Plenary
(734) Building a Data Infrastructure to Enrich the Multiple Sources of Evidence for Humanities Studies: From the Perspective of Cultural Memory // Welcome
Workshops
(168) AI + Informetrics: Multi-disciplinary Interactions in the Era of Big Data
(129) Machine Learning and Artificial Intelligence for Science of Science and Computational Discovery: Principles, Applications, and Future Opportunities
(479) Supporting and Engaging Diverse and Socially Vulnerable Populations with Technology Adoption Amid COVID-19
Overall
Plenary
Workshops
All Events
# artificial intelligence
# Artificial Intelligence
# Technology
17/03/2021 01:00 +00:00 - 17/03/2021 09:00 +00:00
(17/03/2021 01:00 +00:00)
| Workshops | 159 Attendees
(168) AI + Informetrics: Multi-disciplinary Interactions in the Era of Big Data (Workshops)

Keywords: informetrics, artificial intelligence, big data, multi-disciplinary interactions

Inspired by the increasing interactions between informetrics and artificial intelligence (AI) for handling challenges raised from multiple disciplines – e.g., bibliometric-enhanced information retrieval, intelligent bibliometrics, digital library applications, and decision support for science, technology & innovation (ST&I), this workshop is to engage broad audiences to exchange their ideas, concepts, models, and applications in this cutting-edge area, identify research frontiers and emerging topics by incorporating advantages of cross-disciplines, and prompt multi-disciplinary collaboration. This workshop consists of keynotes, oral presentations, and panel discussion, and would attract interests from not only academic researchers and librarians but also decision makers from governments and practical sectors. More information can be addressed on the website: https://ai-informetrics.github.io/, and any enquires please email to Dr Yi Zhang (Yi.Zhang@uts.edu.au).

 

Zhang, Yi (1); Zhang, Chengzhi (2); Mayr, Philipp (3); Suominen, Arho (4,5)

1: University of Technology Sydney, Australia

2: Nanjing University of Science and Technology, China

3: GESIS – Leibniz Institute for the Social Sciences, Germany

4: VTT Technical Research Centre of Finland, Finland; 5: Tampere University, Finland

17/03/2021 10:00 +00:00 - 17/03/2021 12:00 +00:00
(17/03/2021 10:00 +00:00)
| Plenary | 117 Attendees
(734) Building a Data Infrastructure to Enrich the Multiple Sources of Evidence for Humanities Studies: From the Perspective of Cultural Memory // Welcome (Plenary)

The theory of "Social Memory", which originated from "collective memory", systematically separates memory from history. It not only has a great influence on sociology, anthropology, culture and ethnology, but also provides a new perspective for historical research. On the basis of "double sources of evidence method", "triple sources of evidence method" and "quadruple evidence method", it develops "multiple  sources of evidence method" ”. In addition to all kinds of historical books and records, it attaches great importance to folk literature and field investigation, as well as cultural memory resources such as memorials, local chronicles, family genealogies, oral history, private archives, private notes, poems and odes, painting art, gold and stone porcelain, legends and ballads, operas and dramas, festival ceremonies, site relics, and even natural science research achievements such as climate disasters, tree rings and glaciers, All of them can be the sources of evidence and mutual confirmation. Most of these cultural memory resources are stored in libraries, archives, museums, art galleries (GLAM) and other cultural memory institutions.

In the era of Data & Intelligence (big data and machine intelligence), the separation of content and carrier has narrowed the gap between GLAM due to different resource carriers. Data, facts and knowledge have become the smallest unit of "cultural memory". Not only GLAM's cultural memory resources should become parts of the multiple sources of evidence reference system, but also the knowledge graph of people, places, times, events, things and other entities, as well as the quantitative analysis data and visual charts generated from large-scale, long-term, multi-dimensional and fine-grained data also constitute another important source of evidence that can not be ignored and is becoming more and more important in the multiple sources of evidence reference system.

Through the long-term preservation of cultural memory resources, carrier management, knowledge organization, inheritance and dissemination for culture, GLAMs have become the infrastructure of cultural memory and is participating in the work of "building future cultural heritage". In the era of Data & Intelligence, cultural memory institutions have undergone digital transformation, and the construction of "data infrastructure" with "data" as the basic unit has become an important work to support the humanities research and inherit cultural memory. The original definition of "data" is "information that can be transmitted and stored by computer". For humanities research, "data" can be understood as information units that can be processed by machine, such as literature or physical resources, objects, concepts, people, institutions, groups or their structured descriptive information (including variables, values, text symbols or facts, etc.). In addition to the openness, publicity and sustainability of the "infrastructure", the "data infrastructure" should also fully reflect the characteristics of large-scale data, long time coverage, wide geographical scope, fine-grained and muti-dimensional, so as to support the data request, fusion, automatic analysis, statistics and data visualization in a web scale. At the same time, it should be independent of specific application development and specific field research, follow the general data standards and open sharing specification, and become a "data center" between the "back-end" of information infrastructure and the "front-end" of specific field research.

Through theoretical construction and practical exploration, this presentation attempts to elaborate how cultural memory institutions enrich the multiple sources of evidence reference system for humanistic research in the Data & Intelligence age through the construction of data infrastructure.

 

丰富人文研究多重证据参照体系的数据基础设施建设——从文化记忆的角度夏翠娟上海图书馆发源于“集体记忆”的“社会记忆”理论,系统性地将记忆从历史中剥离开来,不仅对社会学、人类学、文化学、民族学产生了巨大的影响,也为史学研究提供了全新的视角,在“二重证据法”、“三重证据法”、“四重证据法”的基础上,发展出了“多重证据法”。表现在除了各种史学典籍之外,重视民间文献和田野调查,且奏章黄册、方志家谱、口述历史、私人档案、私家笔记、诗词歌赋、绘画艺术、金石瓷器、传说歌谣、戏曲戏剧、节日仪式、遗址遗迹等文化记忆资源,甚至气候灾害、树轮冰川等自然科学研究的成果,无不可成为参照和互证的证据。而这些文化记忆资源,大多保存在图书馆、档案馆、博物馆、美术馆(GLAM)等不同文化记忆机构中。数智(大数据和机器智能)时代,内容和载体的分离,缩小了GLAM之间因资源载体不同而造成的差距,数据、事实和知识成了“文化记忆”的最小单位,不仅GLAM的文化记忆资源都应成为多重证据参照体系中的一部分,人、地、时、事、物等实体的知识图谱,以及基于大规模、长时间、多维度、细粒度的数据所生成的量化分析数据、可视化图表等,也构成了多重证据参体系中不可忽视、愈加重要的另一重证据。通过对文化记忆资源的长期保存、载体管理、知识整序和传承传播工作,GLAM都成为了文化记忆的基础设施,都在参与“构建未来的文化遗产”的工作。而在数智时代,文化记忆机构经过数字化转型,建设以“数据”为基本的组成单位的“数据基础设施”,成为支撑人文研究传承文化记忆的重要工作。“数据”最初的定义是“可被计算机传输和存储的信息”,对于人文研究来说,“数据”可理解为可被机器处理的信息单元,如文献或实物资源对象、概念、人物、机构、团体或其结构化的描述信息(包括变量、数值、文字符号或事实等)。“数据基础设施”,除了具备“基础设施”的开放性、公共性和可持续性,还应充分体现数据规模大,覆盖时间长,地域范围广,描述粒度小、维度多等特点,以支持全网域(Webb-scale)的数据调度、融合和自动化分析、统计,和数据可视化。同时还应独立于具体应用开发和特定领域研究之外,遵循通用的数据组织规范和开放共享规范,成为介于信息基础设施“后台”和特定领域研究“前台”之间的“数据中台”本报告试图通过理论建构和实践探索,阐述文化记忆机构如何通过数据基础设施建设来丰富数智时代人文研究的多重证据参照体系。

 

Cuijuan (Jada) Xia (夏翠娟)

17/03/2021 14:00 +00:00 - 17/03/2021 18:00 +00:00
(17/03/2021 14:00 +00:00)
| Workshops | 59 Attendees
(129) Machine Learning and Artificial Intelligence for Science of Science and Computational Discovery: Principles, Applications, and Future Opportunities (Workshops)
Daniel Acuna
Daniel Acuna
Assistant Professor, Syracuse University
TZ
Tong Zeng
Ph.D. Candidate, Nanjing University
HZ
Han Zhuang
Ph.D. Student, Syracuse University
LL
Lizhen Liang
Graduate Student, Syracuse University

Keywords: Machine Learning, Artificial Intelligence, Science of Science, Computational Discovery

Understanding knowledge boundaries, proposing innovative ideas, and producing correct results have become increasingly more competitive in science. Most of these steps rely on colleagues, mentors, and peers. This reliance on humans might not be sustainable because of the growing number of people and ideas entering science. Recent datasets of the scientific enterprise (e.g., full-text publications, citations) offer unprecedented opportunities to solve this scalability issue by using Machine Learning (ML) and Artificial Intelligence (AI). These fields can help Science of Science (SciSci) and Computational Discovery (CD) understand and automate parts of the scientific process. In this workshop, we propose to 1) introduce participants to principles of modern ML and AI, including supervised, unsupervised, and semi-supervised learning, and 2) survey how these techniques are currently used in SciSci and CD. In the end, participants will have a well-rounded understanding of the opportunities and challenges that ML and AI offer. All information about the workshop can be found at https://scienceofscience.org/workshops/

 

Acuna, Daniel (1); Zeng, Tong (2); Zhuang, Han (1); Liang, Lizhen (1)

1: Syracuse University, United States of America

2: School of Information Science, Nanjing University, China

17/03/2021 19:00 +00:00 - 17/03/2021 23:00 +00:00
(17/03/2021 19:00 +00:00)
| Workshops | 65 Attendees
(479) Supporting and Engaging Diverse and Socially Vulnerable Populations with Technology Adoption Amid COVID-19 (Workshops)
Elisabeth Dubois
Elisabeth Dubois
Research Assistant, University at Albany
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
XY
Xiaojun Yuan
DeeDee Marie Bennett Gayle
DeeDee Marie Bennett Gayle
Associate Professor, University at Albany, SUNY

Keywords: socially vulnerable population, technology adoption

Due to inequities in society, certain populations have faced barriers to education and access to resources, which has been accentuated amid the COVID-19 pandemic. These socially vulnerable populations often include underserved and marginalized groups. The COVID-19 pandemic has highlighted many inequities and challenges for said populations especially in regards to technology. Due to the inequities present prior to the pandemic and especially in the face of recovery from the pandemic, a fresh perspective is needed. The workshop will provide a forum for people to discuss key issues and lessons learned on technology adoption among socially vulnerable population during COVID-19. By definition socially vulnerable populations may differ from region to region. In the United States, those often marginalized and underserved include people with disabilities, certain racial and ethnic minorities, older adults, and children, among several other. In general, these populations tend to face disproportionate difficulties before, during, and after major disasters. This multidisciplinary workshop will facilitate lively discussions on the implications of these challenges from a variety of disciplines across an international environment.

 

Yuan, Xiaojun (1); Bennett Gayle, DeeDee (1); Dubois, Elisabeth (1); Wu, Dan (2)

1: University at Albany, United States of America

2: Wuhan University, China

17/03/2021 10:00 +00:00 - 17/03/2021 12:00 +00:00
(17/03/2021 10:00 +00:00)
| Plenary | 117 Attendees
(734) Building a Data Infrastructure to Enrich the Multiple Sources of Evidence for Humanities Studies: From the Perspective of Cultural Memory // Welcome

The theory of "Social Memory", which originated from "collective memory", systematically separates memory from history. It not only has a great influence on sociology, anthropology, culture and ethnology, but also provides a new perspective for historical research. On the basis of "double sources of evidence method", "triple sources of evidence method" and "quadruple evidence method", it develops "multiple  sources of evidence method" ”. In addition to all kinds of historical books and records, it attaches great importance to folk literature and field investigation, as well as cultural memory resources such as memorials, local chronicles, family genealogies, oral history, private archives, private notes, poems and odes, painting art, gold and stone porcelain, legends and ballads, operas and dramas, festival ceremonies, site relics, and even natural science research achievements such as climate disasters, tree rings and glaciers, All of them can be the sources of evidence and mutual confirmation. Most of these cultural memory resources are stored in libraries, archives, museums, art galleries (GLAM) and other cultural memory institutions.

In the era of Data & Intelligence (big data and machine intelligence), the separation of content and carrier has narrowed the gap between GLAM due to different resource carriers. Data, facts and knowledge have become the smallest unit of "cultural memory". Not only GLAM's cultural memory resources should become parts of the multiple sources of evidence reference system, but also the knowledge graph of people, places, times, events, things and other entities, as well as the quantitative analysis data and visual charts generated from large-scale, long-term, multi-dimensional and fine-grained data also constitute another important source of evidence that can not be ignored and is becoming more and more important in the multiple sources of evidence reference system.

Through the long-term preservation of cultural memory resources, carrier management, knowledge organization, inheritance and dissemination for culture, GLAMs have become the infrastructure of cultural memory and is participating in the work of "building future cultural heritage". In the era of Data & Intelligence, cultural memory institutions have undergone digital transformation, and the construction of "data infrastructure" with "data" as the basic unit has become an important work to support the humanities research and inherit cultural memory. The original definition of "data" is "information that can be transmitted and stored by computer". For humanities research, "data" can be understood as information units that can be processed by machine, such as literature or physical resources, objects, concepts, people, institutions, groups or their structured descriptive information (including variables, values, text symbols or facts, etc.). In addition to the openness, publicity and sustainability of the "infrastructure", the "data infrastructure" should also fully reflect the characteristics of large-scale data, long time coverage, wide geographical scope, fine-grained and muti-dimensional, so as to support the data request, fusion, automatic analysis, statistics and data visualization in a web scale. At the same time, it should be independent of specific application development and specific field research, follow the general data standards and open sharing specification, and become a "data center" between the "back-end" of information infrastructure and the "front-end" of specific field research.

Through theoretical construction and practical exploration, this presentation attempts to elaborate how cultural memory institutions enrich the multiple sources of evidence reference system for humanistic research in the Data & Intelligence age through the construction of data infrastructure.

 

丰富人文研究多重证据参照体系的数据基础设施建设——从文化记忆的角度夏翠娟上海图书馆发源于“集体记忆”的“社会记忆”理论,系统性地将记忆从历史中剥离开来,不仅对社会学、人类学、文化学、民族学产生了巨大的影响,也为史学研究提供了全新的视角,在“二重证据法”、“三重证据法”、“四重证据法”的基础上,发展出了“多重证据法”。表现在除了各种史学典籍之外,重视民间文献和田野调查,且奏章黄册、方志家谱、口述历史、私人档案、私家笔记、诗词歌赋、绘画艺术、金石瓷器、传说歌谣、戏曲戏剧、节日仪式、遗址遗迹等文化记忆资源,甚至气候灾害、树轮冰川等自然科学研究的成果,无不可成为参照和互证的证据。而这些文化记忆资源,大多保存在图书馆、档案馆、博物馆、美术馆(GLAM)等不同文化记忆机构中。数智(大数据和机器智能)时代,内容和载体的分离,缩小了GLAM之间因资源载体不同而造成的差距,数据、事实和知识成了“文化记忆”的最小单位,不仅GLAM的文化记忆资源都应成为多重证据参照体系中的一部分,人、地、时、事、物等实体的知识图谱,以及基于大规模、长时间、多维度、细粒度的数据所生成的量化分析数据、可视化图表等,也构成了多重证据参体系中不可忽视、愈加重要的另一重证据。通过对文化记忆资源的长期保存、载体管理、知识整序和传承传播工作,GLAM都成为了文化记忆的基础设施,都在参与“构建未来的文化遗产”的工作。而在数智时代,文化记忆机构经过数字化转型,建设以“数据”为基本的组成单位的“数据基础设施”,成为支撑人文研究传承文化记忆的重要工作。“数据”最初的定义是“可被计算机传输和存储的信息”,对于人文研究来说,“数据”可理解为可被机器处理的信息单元,如文献或实物资源对象、概念、人物、机构、团体或其结构化的描述信息(包括变量、数值、文字符号或事实等)。“数据基础设施”,除了具备“基础设施”的开放性、公共性和可持续性,还应充分体现数据规模大,覆盖时间长,地域范围广,描述粒度小、维度多等特点,以支持全网域(Webb-scale)的数据调度、融合和自动化分析、统计,和数据可视化。同时还应独立于具体应用开发和特定领域研究之外,遵循通用的数据组织规范和开放共享规范,成为介于信息基础设施“后台”和特定领域研究“前台”之间的“数据中台”本报告试图通过理论建构和实践探索,阐述文化记忆机构如何通过数据基础设施建设来丰富数智时代人文研究的多重证据参照体系。

 

Cuijuan (Jada) Xia (夏翠娟)

All Events
# artificial intelligence
# Artificial Intelligence
# Technology
17/03/2021 01:00 +00:00 - 17/03/2021 09:00 +00:00
(17/03/2021 01:00 +00:00)
| Workshops | 159 Attendees
(168) AI + Informetrics: Multi-disciplinary Interactions in the Era of Big Data

Keywords: informetrics, artificial intelligence, big data, multi-disciplinary interactions

Inspired by the increasing interactions between informetrics and artificial intelligence (AI) for handling challenges raised from multiple disciplines – e.g., bibliometric-enhanced information retrieval, intelligent bibliometrics, digital library applications, and decision support for science, technology & innovation (ST&I), this workshop is to engage broad audiences to exchange their ideas, concepts, models, and applications in this cutting-edge area, identify research frontiers and emerging topics by incorporating advantages of cross-disciplines, and prompt multi-disciplinary collaboration. This workshop consists of keynotes, oral presentations, and panel discussion, and would attract interests from not only academic researchers and librarians but also decision makers from governments and practical sectors. More information can be addressed on the website: https://ai-informetrics.github.io/, and any enquires please email to Dr Yi Zhang (Yi.Zhang@uts.edu.au).

 

Zhang, Yi (1); Zhang, Chengzhi (2); Mayr, Philipp (3); Suominen, Arho (4,5)

1: University of Technology Sydney, Australia

2: Nanjing University of Science and Technology, China

3: GESIS – Leibniz Institute for the Social Sciences, Germany

4: VTT Technical Research Centre of Finland, Finland; 5: Tampere University, Finland

17/03/2021 14:00 +00:00 - 17/03/2021 18:00 +00:00
(17/03/2021 14:00 +00:00)
| Workshops | 59 Attendees
(129) Machine Learning and Artificial Intelligence for Science of Science and Computational Discovery: Principles, Applications, and Future Opportunities
Daniel Acuna
Daniel Acuna
Assistant Professor, Syracuse University
TZ
Tong Zeng
Ph.D. Candidate, Nanjing University
HZ
Han Zhuang
Ph.D. Student, Syracuse University
LL
Lizhen Liang
Graduate Student, Syracuse University

Keywords: Machine Learning, Artificial Intelligence, Science of Science, Computational Discovery

Understanding knowledge boundaries, proposing innovative ideas, and producing correct results have become increasingly more competitive in science. Most of these steps rely on colleagues, mentors, and peers. This reliance on humans might not be sustainable because of the growing number of people and ideas entering science. Recent datasets of the scientific enterprise (e.g., full-text publications, citations) offer unprecedented opportunities to solve this scalability issue by using Machine Learning (ML) and Artificial Intelligence (AI). These fields can help Science of Science (SciSci) and Computational Discovery (CD) understand and automate parts of the scientific process. In this workshop, we propose to 1) introduce participants to principles of modern ML and AI, including supervised, unsupervised, and semi-supervised learning, and 2) survey how these techniques are currently used in SciSci and CD. In the end, participants will have a well-rounded understanding of the opportunities and challenges that ML and AI offer. All information about the workshop can be found at https://scienceofscience.org/workshops/

 

Acuna, Daniel (1); Zeng, Tong (2); Zhuang, Han (1); Liang, Lizhen (1)

1: Syracuse University, United States of America

2: School of Information Science, Nanjing University, China

17/03/2021 19:00 +00:00 - 17/03/2021 23:00 +00:00
(17/03/2021 19:00 +00:00)
| Workshops | 65 Attendees
(479) Supporting and Engaging Diverse and Socially Vulnerable Populations with Technology Adoption Amid COVID-19
Elisabeth Dubois
Elisabeth Dubois
Research Assistant, University at Albany
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
XY
Xiaojun Yuan
DeeDee Marie Bennett Gayle
DeeDee Marie Bennett Gayle
Associate Professor, University at Albany, SUNY

Keywords: socially vulnerable population, technology adoption

Due to inequities in society, certain populations have faced barriers to education and access to resources, which has been accentuated amid the COVID-19 pandemic. These socially vulnerable populations often include underserved and marginalized groups. The COVID-19 pandemic has highlighted many inequities and challenges for said populations especially in regards to technology. Due to the inequities present prior to the pandemic and especially in the face of recovery from the pandemic, a fresh perspective is needed. The workshop will provide a forum for people to discuss key issues and lessons learned on technology adoption among socially vulnerable population during COVID-19. By definition socially vulnerable populations may differ from region to region. In the United States, those often marginalized and underserved include people with disabilities, certain racial and ethnic minorities, older adults, and children, among several other. In general, these populations tend to face disproportionate difficulties before, during, and after major disasters. This multidisciplinary workshop will facilitate lively discussions on the implications of these challenges from a variety of disciplines across an international environment.

 

Yuan, Xiaojun (1); Bennett Gayle, DeeDee (1); Dubois, Elisabeth (1); Wu, Dan (2)

1: University at Albany, United States of America

2: Wuhan University, China

Chinese Papers
Chinese Papers 1
Workshops
(526) The Information and Contemplation Salon
Session for Interaction and Engagement (SIE)
(541) i4G - Shaping the iSchools' Identity and Interaction in a Globalized World
(578) Advancing Search Mastery Education: Sharing Experiences & Exploring Possibilities
Poster
Poster 1
Overall
Chinese Papers
Workshops
Session for Interaction and Engagement (SIE)
Poster
All Events
# Chinese Papers
# Search Mastery
# Information
18/03/2021 01:00 +00:00 - 18/03/2021 02:30 +00:00
(18/03/2021 01:00 +00:00)
| Chinese Papers | 42 Attendees
Chinese Papers 1 (Chinese Papers)

(500) Research on the construction of trusted data supporting framework

Keywords: trusted data trusted data supporting trusted data supporting framework framework elements

This study aims to make up for the shortcomings of the research on the framework of trusted data supporting and propose a framework of trusted data supporting based on the definition of “framework”, so as to ensure the development of trusted business and trusted digital society, and further promote the development of Digital China, digital economy and digital society. [Methods / Process] Starting from the concept and connotation of “framework”, this study systematically combs the definition of “framework” which is defined by the International Standardization Organization, identifies the elements of framework and constructs a general framework which also make reference to the elements of the existing data governance framework. Based on the given framework, this study maps and analyzes the existing literature research; Then, this study uses PDCA theory to modify and supplement the proposed framework, explains the relationship between the various elements, and puts forward a scientific and systematic trusted data supporting framework; finally, in this study, the framework is applied to a real case to test its applicability and effectiveness. [Results / Conclusion] This study clarifies the elements of trusted data supporting framework and the relationship between them, and proposes a set of trusted data supporting framework based on the definition of the framework.

 

Feng, Jiaming

School of Information Resource Management, Renmin University of China

 

(185) 专利合作中企业自我中心网络特征对技术创新绩效的影响研究-基于小世界特性的调节作用

Keywords: 专利;合作网络;自我中心网络;小世界;创新绩效

[目的]在专利合作网络小世界特性的调节作用下,分析企业自我中心网络特征对企业技术创新绩效的影响。

[方法]利用企业之间共同专利权人关系构建专利合作网络,以企业申请并授权的专利数量作为企业技术创新绩效的度量,以企业自我中心网络规模、自我中心网络密度和企业合作对象作为自变量,以专利合作网络小世界特性作为调节变量,构建影响企业技术创新绩效的理论模型。

[结果]以语音识别技术领域大公司作为研究样本进行实证分析。使用负二项回归模型进行分析,结果表明:企业自我中心网络规模、企业与小公司合作的比例对技术创新绩效具有显著正向影响;企业自我中心网络密度对技术创新绩效具有显著负向影响。专利合作网络小世界特性在企业自我中心网络规模与创新绩效的影响中没有显著调节作用;专利合作网络小世界特性在企业自我中心网络密度与创新绩效的影响中有显著正向调节作用,进一步分析可得:起到正向调节作用的是聚集系数,路径长度虽然起到负向调节作用,但并不显著。

[局限]只针对语音识别技术领域展开研究,还需进一步扩大研究样本,以验证研究结果的普适性;只将企业列为研究对象,对于其他创新主体如高校、科研院所等缺乏研究。

[结论]通过实证分析揭示了企业自我中心网络特征对企业技术创新绩效的影响,理清了专利合作网络小世界特性影响企业技术创新绩效的机制,小世界网络通过其高聚集系数增强了企业自我中心网络密度对企业创新绩效的负向影响。针对分析结果,提出提升企业技术创新绩效的对策和建议。

 

Guan, Peng (1); Wang, Yuefen (2)

1: Chaohu University, China, People's Republic of

2: Nanjing University of Science & Technology, China, People's Republic of

 

(238) 基于知识网络强弱关系变迁测度新兴主题的不确定性分析

未来发展的不确定性是新兴研究主题一个重要特征,不确定性趋势预测对新兴研究主题的发展规划尤为关键。本文首先综述了新兴主题的未来不确定性分析及其测度方法,并调研了科学发现过程中的不确定性及其测度方法。之后,本文提出在结合新兴研究主题识别的基础上,通过观察社区数量、弱关联数量、强关联数量的变化规律预测新兴技术主题未来发展的不确定性。最后,通过干细胞领域的实证分析证明了本文方法可以在一定程度上实现新兴研究主题未来发展不确定性的测度。本研究方法可以为新兴前沿主题的科技政策规划提供有效支撑。

 

Xu, Haiyun (1,2); Yue, Zenghui (3); Chen, Liang (2); Yang, Guancan (4); Cheng, Junmo (1)

1: Business School, Shandong University of Technology, China, People's Republic of

2: Institute of Scientific and Technical Information of China

3: School of Medical Information Engineering, Jining Medical University

4: School of Information Resource Management, Renmin University of China

 

(606) Research on the Information Needs of University Freshmen in the Adaptation Stage Based on Kano Model

Based on Kano model, this paper analyzes the information needs of universities students in the freshmen's adaptation stage. Through semi-structured in-depth interview and text coding analysis, 13 aspects of Freshmen's adaptation stage are obtained, and 16 information needs that colleges and universities can provide corresponding services are determined. Through the Kano questionnaire to investigate the information needs, using three kinds of Kano frequency statistical methods, we get 13 one-dimensional requirements and 3 attractive requirements, and of which three are mixed type; through the calculation of Better-Worse index and average satisfaction, combined with quadrant analysis, we get the priority of each demand element. Based on the results of interview and questionnaire analysis, this paper analyzes the current situation and shortcomings of information service in universities, and puts forward some strategies to improve the service. The research is helpful for colleges and universities to understand the information needs of freshmen, and take measures to improve the information service for freshmen gradually.

 

Xing, Chang (1); Xiao, Xue (2)

1: Tianjin Nankai High School, China, People’s Republic of

2: Nankai University, China, People's Republic of

18/03/2021 10:30 +00:00 - 18/03/2021 12:00 +00:00
(18/03/2021 10:30 +00:00)
| Poster | 72 Attendees
Poster 1 (Poster)

Please go to the Presentation Library to view posters, watch recordings, and talk to the presenters.

18/03/2021 13:00 +00:00 - 18/03/2021 15:00 +00:00
(18/03/2021 13:00 +00:00)
| Session for Interaction and Engagement (SIE) | 66 Attendees
(541) i4G - Shaping the iSchools' Identity and Interaction in a Globalized World (Session for Interaction and Engagement (SIE))
Ben Kaden
Ben Kaden
Researcher, Berlin School of Library and Information Science Humboldt-Universität zu Berlin
VP
Vivien Petras
Humboldt-Universität zu Berlin
GM
Gary Marchionini
GC
Gobinda Chowdhury
University of Strathclyde
Michael Kleineberg
Michael Kleineberg
Researcher, Berlin School of Library and Information Science (Humboldt-Universität zu Berlin)
Michael Seadle
Michael Seadle
Executive Director, iSchools Inc.
Di. Wang
Di. Wang
Postdoc Researcher, Wuhan University
LZ
Lihong Zhou
Associate Dean, School of Information Management, Wuhan University
Leslie Thomson
Leslie Thomson
Postdoctoral Research Associate, University of North Carolina at Chapel Hill
MI
Maryam Idris Bugaje
University of Strathclyde

In 2020/2021, the i4G-project, funded by the Mellon Foundation conducted a comprehensive study on the current situation of the iSchools organization in relation to the field of information and its place within society as well as the organizational, political, economical, and societal structures iSchools operate in. Of course, the year 2020 posed an additional and very forceful challenge in form of the Covid-19-pandemic, which markedly informed our activities and the study as well. The panel will present significant findings of this study in special regard to our experiences during the special situation in 2020. As both, the insights identified by our study and the aftereffects of the pandemic turn out to be very eventful to the iSchools community, we will expand the presentation with a broader discussion and an annotateable document aimed to transform the panel in a continuous discourse.

 

Kaden, Ben (1); Petras, Vivien (1); Marchionini, Gary (2); Thomson, Leslie (2); Bugaje, Maryam (3); Chowdhury, Gobinda (3); Kleineberg, Michael (1); Seadle, Michael (1); Wang, Di (4); Zhou, Lihong (4)

1: Humboldt-Universität zu Berlin, Germany

2: UNC School of Information & Library Science

3: Department of Computer & Information Sciences (iSchool) University of Strathclyde

4: WHU School of Information Management Wuhan University

18/03/2021 17:30 +00:00 - 18/03/2021 19:00 +00:00
(18/03/2021 17:30 +00:00)
| Session for Interaction and Engagement (SIE) | 25 Attendees
(578) Advancing Search Mastery Education: Sharing Experiences & Exploring Possibilities (Session for Interaction and Engagement (SIE))
Brian Butler
Brian Butler
Professor and Senior Associate Dean, University of Maryland
Morgan Adle
Morgan Adle
MLIS Program Manager & PhD Student, University of Maryland
Sarah McGrew
Sarah McGrew
Assistant Professor, University of Maryland, College Park
Ryan O'Grady
Ryan O'Grady
Beth St.  Jean
Beth St. Jean
Associate Professor, University of Maryland College of Information Studies

Search mastery refers to students’ knowledge, skills, and abilities to optimally use and critically evaluate publicly available search platforms to discover and select documents, images, video, and data needed for problem-solving and decision-making. While search mastery constitutes only a small subset of the topics considered in a comprehensive information literacy education program, its centrality in almost every aspect of modern society makes it a critical aspect of student success both in academia and beyond. The goals of the proposed session are to increase participants’ knowledge of strategies for assessing and teaching search skills within particular courses, through co-curricular activities, and across the curriculum of an academic program. Session participants will share observations and data they have about their students’ level of search mastery; exchange lessons-learned from efforts to develop search mastery, and develop creative approaches for improving the students’ search knowledge and skills in their courses and programs.

 

Butler, Brian; Adle, Morgan; Gorham, Ursula; McGrew, Sarah; O'Grady, Ryan; Roderer, Nancy; St. Jean, Beth

University of Maryland, United States of America

18/03/2021 20:00 +00:00 - 19/03/2021 00:00 +00:00
(18/03/2021 20:00 +00:00 - 19/03/2021 00:00 +00:00)
| Workshops | 18 Attendees
(526) The Information and Contemplation Salon (Workshops)
RC
Roger Chabot
Western University
Tim Gorichanaz
Tim Gorichanaz
Assistant Teaching Professor, Drexel University
Jenna Hartel
Jenna Hartel
Associate Professor, Faculty of Information, University of Toronto
HS
Hugh Samson
Graduate Student, Faculty of Information, University of Toronto
Kiersten F. Latham
Kiersten F. Latham
Director & Associate Professor, Michigan State University

Keywords: Information, Contemplation, Contemplative Inquiry

This hands-on workshop invites participants to entertain the merits of "contemplation" as a new frontier for the iSchool community. Founding members of the Information and Contemplation Salon - a virtual research group - will introduce concepts at the crossroads of information and contemplation, each serving as a point of departure for dynamic discussion that is then encapsulated and experienced through a virtual activity. Topics include: the emerging discipline of Contemplative Studies; Contemplation as Information Behaviour; The Tree of Contemplative Practices; Contemplative Infrastructure; and Intellectual Humility. This workshop will be offered in the spirit of Contemplative Pedagogy, which honors an egalitarian, holistic, and uplifting learning environment. Participants will be gently immersed in an alternative universe of information-related concepts and leave with a new perspective.

 

Chabot, Roger (1); Gorichanaz, Tim (2); Hartel, Jenna (3); Latham, Kiersten (4); Samson, Hugh (3); Stoner, Madison (3)

1: University of Western Ontario, Canada

2: Drexel University, USA

3: University of Toronto

4: Michigan State University, USA

18/03/2021 01:00 +00:00 - 18/03/2021 02:30 +00:00
(18/03/2021 01:00 +00:00)
| Chinese Papers | 42 Attendees
Chinese Papers 1

(500) Research on the construction of trusted data supporting framework

Keywords: trusted data trusted data supporting trusted data supporting framework framework elements

This study aims to make up for the shortcomings of the research on the framework of trusted data supporting and propose a framework of trusted data supporting based on the definition of “framework”, so as to ensure the development of trusted business and trusted digital society, and further promote the development of Digital China, digital economy and digital society. [Methods / Process] Starting from the concept and connotation of “framework”, this study systematically combs the definition of “framework” which is defined by the International Standardization Organization, identifies the elements of framework and constructs a general framework which also make reference to the elements of the existing data governance framework. Based on the given framework, this study maps and analyzes the existing literature research; Then, this study uses PDCA theory to modify and supplement the proposed framework, explains the relationship between the various elements, and puts forward a scientific and systematic trusted data supporting framework; finally, in this study, the framework is applied to a real case to test its applicability and effectiveness. [Results / Conclusion] This study clarifies the elements of trusted data supporting framework and the relationship between them, and proposes a set of trusted data supporting framework based on the definition of the framework.

 

Feng, Jiaming

School of Information Resource Management, Renmin University of China

 

(185) 专利合作中企业自我中心网络特征对技术创新绩效的影响研究-基于小世界特性的调节作用

Keywords: 专利;合作网络;自我中心网络;小世界;创新绩效

[目的]在专利合作网络小世界特性的调节作用下,分析企业自我中心网络特征对企业技术创新绩效的影响。

[方法]利用企业之间共同专利权人关系构建专利合作网络,以企业申请并授权的专利数量作为企业技术创新绩效的度量,以企业自我中心网络规模、自我中心网络密度和企业合作对象作为自变量,以专利合作网络小世界特性作为调节变量,构建影响企业技术创新绩效的理论模型。

[结果]以语音识别技术领域大公司作为研究样本进行实证分析。使用负二项回归模型进行分析,结果表明:企业自我中心网络规模、企业与小公司合作的比例对技术创新绩效具有显著正向影响;企业自我中心网络密度对技术创新绩效具有显著负向影响。专利合作网络小世界特性在企业自我中心网络规模与创新绩效的影响中没有显著调节作用;专利合作网络小世界特性在企业自我中心网络密度与创新绩效的影响中有显著正向调节作用,进一步分析可得:起到正向调节作用的是聚集系数,路径长度虽然起到负向调节作用,但并不显著。

[局限]只针对语音识别技术领域展开研究,还需进一步扩大研究样本,以验证研究结果的普适性;只将企业列为研究对象,对于其他创新主体如高校、科研院所等缺乏研究。

[结论]通过实证分析揭示了企业自我中心网络特征对企业技术创新绩效的影响,理清了专利合作网络小世界特性影响企业技术创新绩效的机制,小世界网络通过其高聚集系数增强了企业自我中心网络密度对企业创新绩效的负向影响。针对分析结果,提出提升企业技术创新绩效的对策和建议。

 

Guan, Peng (1); Wang, Yuefen (2)

1: Chaohu University, China, People's Republic of

2: Nanjing University of Science & Technology, China, People's Republic of

 

(238) 基于知识网络强弱关系变迁测度新兴主题的不确定性分析

未来发展的不确定性是新兴研究主题一个重要特征,不确定性趋势预测对新兴研究主题的发展规划尤为关键。本文首先综述了新兴主题的未来不确定性分析及其测度方法,并调研了科学发现过程中的不确定性及其测度方法。之后,本文提出在结合新兴研究主题识别的基础上,通过观察社区数量、弱关联数量、强关联数量的变化规律预测新兴技术主题未来发展的不确定性。最后,通过干细胞领域的实证分析证明了本文方法可以在一定程度上实现新兴研究主题未来发展不确定性的测度。本研究方法可以为新兴前沿主题的科技政策规划提供有效支撑。

 

Xu, Haiyun (1,2); Yue, Zenghui (3); Chen, Liang (2); Yang, Guancan (4); Cheng, Junmo (1)

1: Business School, Shandong University of Technology, China, People's Republic of

2: Institute of Scientific and Technical Information of China

3: School of Medical Information Engineering, Jining Medical University

4: School of Information Resource Management, Renmin University of China

 

(606) Research on the Information Needs of University Freshmen in the Adaptation Stage Based on Kano Model

Based on Kano model, this paper analyzes the information needs of universities students in the freshmen's adaptation stage. Through semi-structured in-depth interview and text coding analysis, 13 aspects of Freshmen's adaptation stage are obtained, and 16 information needs that colleges and universities can provide corresponding services are determined. Through the Kano questionnaire to investigate the information needs, using three kinds of Kano frequency statistical methods, we get 13 one-dimensional requirements and 3 attractive requirements, and of which three are mixed type; through the calculation of Better-Worse index and average satisfaction, combined with quadrant analysis, we get the priority of each demand element. Based on the results of interview and questionnaire analysis, this paper analyzes the current situation and shortcomings of information service in universities, and puts forward some strategies to improve the service. The research is helpful for colleges and universities to understand the information needs of freshmen, and take measures to improve the information service for freshmen gradually.

 

Xing, Chang (1); Xiao, Xue (2)

1: Tianjin Nankai High School, China, People’s Republic of

2: Nankai University, China, People's Republic of

18/03/2021 20:00 +00:00 - 19/03/2021 00:00 +00:00
(18/03/2021 20:00 +00:00 - 19/03/2021 00:00 +00:00)
| Workshops | 18 Attendees
(526) The Information and Contemplation Salon
RC
Roger Chabot
Western University
Tim Gorichanaz
Tim Gorichanaz
Assistant Teaching Professor, Drexel University
Jenna Hartel
Jenna Hartel
Associate Professor, Faculty of Information, University of Toronto
HS
Hugh Samson
Graduate Student, Faculty of Information, University of Toronto
Kiersten F. Latham
Kiersten F. Latham
Director & Associate Professor, Michigan State University

Keywords: Information, Contemplation, Contemplative Inquiry

This hands-on workshop invites participants to entertain the merits of "contemplation" as a new frontier for the iSchool community. Founding members of the Information and Contemplation Salon - a virtual research group - will introduce concepts at the crossroads of information and contemplation, each serving as a point of departure for dynamic discussion that is then encapsulated and experienced through a virtual activity. Topics include: the emerging discipline of Contemplative Studies; Contemplation as Information Behaviour; The Tree of Contemplative Practices; Contemplative Infrastructure; and Intellectual Humility. This workshop will be offered in the spirit of Contemplative Pedagogy, which honors an egalitarian, holistic, and uplifting learning environment. Participants will be gently immersed in an alternative universe of information-related concepts and leave with a new perspective.

 

Chabot, Roger (1); Gorichanaz, Tim (2); Hartel, Jenna (3); Latham, Kiersten (4); Samson, Hugh (3); Stoner, Madison (3)

1: University of Western Ontario, Canada

2: Drexel University, USA

3: University of Toronto

4: Michigan State University, USA

18/03/2021 13:00 +00:00 - 18/03/2021 15:00 +00:00
(18/03/2021 13:00 +00:00)
| Session for Interaction and Engagement (SIE) | 66 Attendees
(541) i4G - Shaping the iSchools' Identity and Interaction in a Globalized World
Ben Kaden
Ben Kaden
Researcher, Berlin School of Library and Information Science Humboldt-Universität zu Berlin
VP
Vivien Petras
Humboldt-Universität zu Berlin
GM
Gary Marchionini
GC
Gobinda Chowdhury
University of Strathclyde
Michael Kleineberg
Michael Kleineberg
Researcher, Berlin School of Library and Information Science (Humboldt-Universität zu Berlin)
Michael Seadle
Michael Seadle
Executive Director, iSchools Inc.
Di. Wang
Di. Wang
Postdoc Researcher, Wuhan University
LZ
Lihong Zhou
Associate Dean, School of Information Management, Wuhan University
Leslie Thomson
Leslie Thomson
Postdoctoral Research Associate, University of North Carolina at Chapel Hill
MI
Maryam Idris Bugaje
University of Strathclyde

In 2020/2021, the i4G-project, funded by the Mellon Foundation conducted a comprehensive study on the current situation of the iSchools organization in relation to the field of information and its place within society as well as the organizational, political, economical, and societal structures iSchools operate in. Of course, the year 2020 posed an additional and very forceful challenge in form of the Covid-19-pandemic, which markedly informed our activities and the study as well. The panel will present significant findings of this study in special regard to our experiences during the special situation in 2020. As both, the insights identified by our study and the aftereffects of the pandemic turn out to be very eventful to the iSchools community, we will expand the presentation with a broader discussion and an annotateable document aimed to transform the panel in a continuous discourse.

 

Kaden, Ben (1); Petras, Vivien (1); Marchionini, Gary (2); Thomson, Leslie (2); Bugaje, Maryam (3); Chowdhury, Gobinda (3); Kleineberg, Michael (1); Seadle, Michael (1); Wang, Di (4); Zhou, Lihong (4)

1: Humboldt-Universität zu Berlin, Germany

2: UNC School of Information & Library Science

3: Department of Computer & Information Sciences (iSchool) University of Strathclyde

4: WHU School of Information Management Wuhan University

18/03/2021 17:30 +00:00 - 18/03/2021 19:00 +00:00
(18/03/2021 17:30 +00:00)
| Session for Interaction and Engagement (SIE) | 25 Attendees
(578) Advancing Search Mastery Education: Sharing Experiences & Exploring Possibilities
Brian Butler
Brian Butler
Professor and Senior Associate Dean, University of Maryland
Morgan Adle
Morgan Adle
MLIS Program Manager & PhD Student, University of Maryland
Sarah McGrew
Sarah McGrew
Assistant Professor, University of Maryland, College Park
Ryan O'Grady
Ryan O'Grady
Beth St.  Jean
Beth St. Jean
Associate Professor, University of Maryland College of Information Studies

Search mastery refers to students’ knowledge, skills, and abilities to optimally use and critically evaluate publicly available search platforms to discover and select documents, images, video, and data needed for problem-solving and decision-making. While search mastery constitutes only a small subset of the topics considered in a comprehensive information literacy education program, its centrality in almost every aspect of modern society makes it a critical aspect of student success both in academia and beyond. The goals of the proposed session are to increase participants’ knowledge of strategies for assessing and teaching search skills within particular courses, through co-curricular activities, and across the curriculum of an academic program. Session participants will share observations and data they have about their students’ level of search mastery; exchange lessons-learned from efforts to develop search mastery, and develop creative approaches for improving the students’ search knowledge and skills in their courses and programs.

 

Butler, Brian; Adle, Morgan; Gorham, Ursula; McGrew, Sarah; O'Grady, Ryan; Roderer, Nancy; St. Jean, Beth

University of Maryland, United States of America

18/03/2021 10:30 +00:00 - 18/03/2021 12:00 +00:00
(18/03/2021 10:30 +00:00)
| Poster | 72 Attendees
Poster 1

Please go to the Presentation Library to view posters, watch recordings, and talk to the presenters.

Workshops
(564) Understanding the big data in emergency management: agenda for future research
(559) Navigating through the Panoply of Provenance Metadata Standards
Session for Interaction and Engagement (SIE)
(245) A Knowledge Management Approach to Covid-19 Application Development
Student Symposium
Student Symposium
Overall
Workshops
Session for Interaction and Engagement (SIE)
Student Symposium
All Events
# Big Data
# COVID-19
# Provenance
19/03/2021 01:00 +00:00 - 19/03/2021 05:00 +00:00
(19/03/2021 01:00 +00:00)
| Session for Interaction and Engagement (SIE) | 50 Attendees
(245) A Knowledge Management Approach to Covid-19 Application Development (Session for Interaction and Engagement (SIE))
YZ
Yao Zhang
Assistant Professor, Nankai University
WE
William Edgar
Adjunct Faculty, Kent State University
KA
Kendra Albright
Goodyear Endowed Professor in Knowledge Management, Kent State University
XL
Xuguang Li

The Covid-19 pandemic has posed great challenges worldwide. Compared with other groups, older adults are less likely to benefit from online knowledge resources about this virus because of their limited access and health literacy, and usability issues arising from their physical limitations. Knowledge management (KM) refers to the process of creating, sharing, and storing information to maximize its usefulness to a specific group. A KM approach is useful to create and implement a Covid-19 application for older adults to address these challenges. This session will integrate KM theories and practices to develop an application to meet the information needs and to improve the user experience of older adults. Participants will work in groups to create different, competing versions of the application. The different versions will then be reviewed by all participants and integrated by consensus into a single application.

 

Zhang, Yao (1); Edgar, William B. (2); Albright, Kendra (2); Li, Xuguang (1)

1: Nankai University, China, People's Republic of

2: Kent State University, USA

19/03/2021 09:00 +00:00 - 19/03/2021 12:00 +00:00
(19/03/2021 09:00 +00:00)
| Workshops | 61 Attendees
(564) Understanding the big data in emergency management: agenda for future research (Workshops)
ZZ
Ziqi Zhang
Lecturer, University of Sheffield
MR
Ming Ren
Beijing, Renmin University of China
XW
Xianhua Wu
Shanghai Maritime University
JZ
Jun Zhang
University of Sheffield

Keywords: big data, emergency management, research agenda

Big data are playing a more and more important role in the lifecycle of emergency management. The workshop aims to develop a deep understanding of the multi-dimensional disparate data sources used in the emergency management and identify key trends that inform future research agendas and practices. Through two talks and a group discussion session, it is hoped to strengthen a multidisciplinary network consisting of academic researchers, practitioners and policy makers with interest and/or involvement in the intersection of big data and emergency management.

 

Ren, Ming (1); Zhang, Ziqi (2); Li, Guozhi (3); Wu, Xianhua (4); Zhang, Jun (2)

1: Renmin University of China, China, People's Republic of

2: University of Sheffield, UK

3: Beijing Jianghe RichWay Technology Development, China, People's Republic of

4: Shanghai Maritime University, China, People's Republic of

19/03/2021 12:00 +00:00 - 19/03/2021 16:00 +00:00
(19/03/2021 12:00 +00:00)
| Student Symposium | 52 Attendees
Student Symposium (Student Symposium)

At the Student Symposium undergraduate and master’s students will present their recent research in a friendly and constructive environment. Students from around the world will share their research projects, receive feedback and engage in discussion.

Participation in the Student Symposium, is restricted to individuals who applied for this event in advance and were accepted. The Student Symposium is not open to observers.

19/03/2021 13:30 +00:00 - 19/03/2021 21:30 +00:00
(19/03/2021 13:30 +00:00)
| Workshops | 28 Attendees
(559) Navigating through the Panoply of Provenance Metadata Standards (Workshops)

Keywords: Provenance; Workflows; Curation; Preservation; Metadata Cross-walking

The following provenance models and metadata standards will be discussed and evaluated using real-world research data provided by the organizers. Emphasis will be placed on highlighting the strengths and capabilities of each model, as well as shortcomings of any individual model which are handled by one or more of the others. The morning session will cover the models while the afternoon session will provide hands-on cross-walking exercises to explore the modeling differences in greater depth.

- PREMIS: This is an international metadata standard developed by Library of Congress to support digital curation and preservation. https://www.loc.gov/standards/premis/

- PROV: PROV is a family of models and standards proposed by the W3C. It is used to document provenance information of data and digital objects. https://www.w3.org/TR/prov-overview/

- ProvONE: This is an extension model of PROV which includes concepts and attributes for specifying workflows and data products produced by their execution. https://purl.dataone.org/provone-v1-dev

 

Bettivia, Rhiannon (1); Cheng, Jessica Yi-Yun (2); Gryk, Michael Robert (2)

1: Simmons University, Boston, United States of America

2: University of Illinois, Urbana-Champaign, United States of America

All Events
# Big Data
# Provenance
19/03/2021 09:00 +00:00 - 19/03/2021 12:00 +00:00
(19/03/2021 09:00 +00:00)
| Workshops | 61 Attendees
(564) Understanding the big data in emergency management: agenda for future research
ZZ
Ziqi Zhang
Lecturer, University of Sheffield
MR
Ming Ren
Beijing, Renmin University of China
XW
Xianhua Wu
Shanghai Maritime University
JZ
Jun Zhang
University of Sheffield

Keywords: big data, emergency management, research agenda

Big data are playing a more and more important role in the lifecycle of emergency management. The workshop aims to develop a deep understanding of the multi-dimensional disparate data sources used in the emergency management and identify key trends that inform future research agendas and practices. Through two talks and a group discussion session, it is hoped to strengthen a multidisciplinary network consisting of academic researchers, practitioners and policy makers with interest and/or involvement in the intersection of big data and emergency management.

 

Ren, Ming (1); Zhang, Ziqi (2); Li, Guozhi (3); Wu, Xianhua (4); Zhang, Jun (2)

1: Renmin University of China, China, People's Republic of

2: University of Sheffield, UK

3: Beijing Jianghe RichWay Technology Development, China, People's Republic of

4: Shanghai Maritime University, China, People's Republic of

19/03/2021 13:30 +00:00 - 19/03/2021 21:30 +00:00
(19/03/2021 13:30 +00:00)
| Workshops | 28 Attendees
(559) Navigating through the Panoply of Provenance Metadata Standards

Keywords: Provenance; Workflows; Curation; Preservation; Metadata Cross-walking

The following provenance models and metadata standards will be discussed and evaluated using real-world research data provided by the organizers. Emphasis will be placed on highlighting the strengths and capabilities of each model, as well as shortcomings of any individual model which are handled by one or more of the others. The morning session will cover the models while the afternoon session will provide hands-on cross-walking exercises to explore the modeling differences in greater depth.

- PREMIS: This is an international metadata standard developed by Library of Congress to support digital curation and preservation. https://www.loc.gov/standards/premis/

- PROV: PROV is a family of models and standards proposed by the W3C. It is used to document provenance information of data and digital objects. https://www.w3.org/TR/prov-overview/

- ProvONE: This is an extension model of PROV which includes concepts and attributes for specifying workflows and data products produced by their execution. https://purl.dataone.org/provone-v1-dev

 

Bettivia, Rhiannon (1); Cheng, Jessica Yi-Yun (2); Gryk, Michael Robert (2)

1: Simmons University, Boston, United States of America

2: University of Illinois, Urbana-Champaign, United States of America

19/03/2021 01:00 +00:00 - 19/03/2021 05:00 +00:00
(19/03/2021 01:00 +00:00)
| Session for Interaction and Engagement (SIE) | 50 Attendees
(245) A Knowledge Management Approach to Covid-19 Application Development
YZ
Yao Zhang
Assistant Professor, Nankai University
WE
William Edgar
Adjunct Faculty, Kent State University
KA
Kendra Albright
Goodyear Endowed Professor in Knowledge Management, Kent State University
XL
Xuguang Li

The Covid-19 pandemic has posed great challenges worldwide. Compared with other groups, older adults are less likely to benefit from online knowledge resources about this virus because of their limited access and health literacy, and usability issues arising from their physical limitations. Knowledge management (KM) refers to the process of creating, sharing, and storing information to maximize its usefulness to a specific group. A KM approach is useful to create and implement a Covid-19 application for older adults to address these challenges. This session will integrate KM theories and practices to develop an application to meet the information needs and to improve the user experience of older adults. Participants will work in groups to create different, competing versions of the application. The different versions will then be reviewed by all participants and integrated by consensus into a single application.

 

Zhang, Yao (1); Edgar, William B. (2); Albright, Kendra (2); Li, Xuguang (1)

1: Nankai University, China, People's Republic of

2: Kent State University, USA

19/03/2021 12:00 +00:00 - 19/03/2021 16:00 +00:00
(19/03/2021 12:00 +00:00)
| Student Symposium | 52 Attendees
Student Symposium

At the Student Symposium undergraduate and master’s students will present their recent research in a friendly and constructive environment. Students from around the world will share their research projects, receive feedback and engage in discussion.

Participation in the Student Symposium, is restricted to individuals who applied for this event in advance and were accepted. The Student Symposium is not open to observers.

Plenary
(735) Georgia Tech’s online Master in Computer Science Program and the future of online learning
Full Research Papers
Full Research Papers 1
Full Research Papers 2
Full Research Papers 3
Full Research Papers 4
Short Research Papers
Short Research Papers 1
Chinese Papers
Chinese Papers 2
Chinese Papers 3
Chinese Papers 4
Virtual Interactive Session (VIS)
(481) Just put it on Zoom!: Effectively Fostering a Virtual Intellectual Community Part 1
Overall
Plenary
Full Research Papers
Short Research Papers
Chinese Papers
Virtual Interactive Session (VIS)
22/03/2021 01:00 +00:00 - 22/03/2021 02:30 +00:00
(22/03/2021 01:00 +00:00)
| Chinese Papers | 33 Attendees
Chinese Papers 2 (Chinese Papers)

(590) 国外档案学学科建设与发展领域分析及启示 ——基于对55所院校的调查

Keywords: 国外档案学, 学科建设, 发展领域, 学科独立性, 中国特色档案学

跟踪了解国外档案学学科建设和发展的最新动向,可以为我国档案学学科建设和发展提供参考和洞见。本研究对国外55所重点院校档案学专业的学科点设置、学位设置和重点发展领域进行了调研分析。研究发现,国外档案学学科建设与发展具有注重学科融合发展、以职业教育为重要导向、学科独立性较弱和开阔的档案社会化研究视野等特征。基于此,提出我国档案学学科建设发展的建议:加强学科融合发展,强化综合能力培养;重视职业导向教育,打造多元融合的人才培养体系;保持学科独立性,发展中国特色档案学教育;关注社会视角下的档案事业发展,增添人文关怀。

 

Wang, Ning; Li, Mengqiu

Renmin University of China, China, People's Republic of China

 

(524) 多元融合视域下学术期刊话语权评价研究——以中国英文学术期刊为例

Keywords: 学术期刊;话语权评价;话语影响力;话语引导力;科学计量学;Altmetrics

本文基于评价科学理论、话语权理论和传播学理论,首先探讨了学术期刊话语权评价的基本问题:界定了学术话语权和学术期刊话语权等概念内涵;提出了学术期刊话语权由话语影响力和话语引导力维度构成,话语影响力由话语影响能力和话语影响权力要素组成,话语引导力由新闻话语、社交媒体话语、同行评议话语、百科话语、视频话语以及政策话语引导等要素组成;探究了学术期刊话语权形成过程和运作机理;构建了中国英文学术期刊话语权评价模型;其次融合多源异构数据,采用相关分析、集成因子分析、熵权法、TOPSIS法以及二维映射法优势,从多维度、多要素、多指标、多方法融合、比较和评估视角进行了中国英文学术期刊话语权评价实证研究。结果表明,本文按照理论、方法与应用逻辑展开多元融合的学术期刊话语权评价研究具有一定的实用性、兼顾性和可靠性。本文旨在为我国学术期刊话语权评价和管理决策、创建世界一流学术期刊,进而提升中国学术期刊话语权提供参考。

 

Wang, Xu

School of Economics and Management, Yanshan University, China, People's Republic of

 

(542) 结合巴斯扩散模型及SIR模型的微信公众号内容传播特征分析

Keywords: 微信公众号, 信息传播, 巴斯扩散模型, SIR模型

微信公众号内容的传播包括两条扩散路径:公众号直接将信息推送给其订阅用户产生首轮的传播以及非公众号订阅用户通过其它用户的转发与传播接触信息。本研究通过对微信公众号内容传播过程的分析,提出了结合巴斯扩散模型和SIR传染病模型的公众号传播模型,用以揭示其内容的传播规律。本研究利用“图情会”公众号阅读数据对模型进行KS检验,结果显示,模型总体上能够对公众号内容的传播过程进行模拟。研究通过对模型中参数及模型初始条件进行分析发现,已分享过的读者不再进行分享的概率,以及非公众号订阅用户从其它人转发中接触到信息的概率对公众号内容在目标群体中的扩散范围有较大影响;高阅读量的公众号内容往往在内容上有“破圈”的特性,往往能吸引到更多非订阅用户进行阅读,具有更广的传播范围。

 

Yang, SiLuo; Xiao, AoXia

School of Information Management, Wuhan University, China

22/03/2021 03:30 +00:00 - 22/03/2021 05:00 +00:00
(22/03/2021 03:30 +00:00)
| Chinese Papers | 24 Attendees
Chinese Papers 3 (Chinese Papers)

(513) A components framework conception for big data governance rules

Keywords: big data governance; big data governance rules; the components framework for rules

This research clarifies the relevant concepts of big data governance rules and proposes the framework of the components of big data governance rules, which aims to provide reference for the research of big data governance rules and guidance for the practice of big data governance. [Method/process] Using the method of literature survey, this paper reviews the existing relevant research, combs the relevant disciplines and governance rules, studies the components of big data governance rules and the relationship between them, and uses the methods of policy analysis and case study to map and verify the components of big data governance rules in national policies. [Result/conclusion] From the perspective of theoretical basis and analysis, this paper puts forward 15 components of big data governance rules including governance benefit components from four mapping dimensions and discusses the relationship between different components and the direction of future research and practice.

 

Jie, Huang

Renmin University of China, China, People's Republic of

 

(556) The current situation, problems and Countermeasures of Digital Humanities Education in China from the perspective of students

Keywords: Digital Humanities Education; Digital Humanities; Talent Training; The Perspective of Students

This paper describes the current situation of digital humanities education in China, reveals problems and proposes corresponding solutions from the perspective of students, aiming to provide enlightenment and reference for digital humanities education practice.

Design/methodology/approach - Taking the digital humanities education practice of Renmin University of China as a case, this paper uses code analysis to process data.

Findings - In the current digital humanities education, there are two different demands and training goals of "humanities who understand technology" and "technical experts who understand humanities"; there is a significant information asymmetry between education providers and students; the humanistic characteristics are outstanding but the technology is still weak; the project-based teaching has achieved good results, but the substantive guidance and assistance from the education provider is relatively less; the interdisciplinary communication and cooperation of the student project team are facing many challenges and the students lack effective feedback channels.

Original value - This paper describes the current situation of digital humanities education in China, reveals problems and proposes corresponding solutions from the perspective of student

 

He, Siyuan; Zhang, Chenwen; Ga, Lasen; Pei, Junliang

Renmin; University of China

 

(575) Research on the prediction of 5G patent value at home and abroad

Keywords: patent value, 5G, technology life cycle, XGBoost; prediction

This study aims to build a patent value evaluation system, and prospectively predict high-value patents. [Design/Methodology] Based on the patent data related to 5G technology in the Incopat patent database, we comprehensively considered the internal and external factors of the value of 5G patents, and used the Logistic model to visualize the technology life cycle of 5G patents at home and abroad. We built a patent value prediction model that includes patented technical features, market features, legal features, and patentee features. We used random forest, decision tree and XGBoost algorithm for training and evaluation. Finally, we tuned the model parameters and calculated the importance of different features in patent value prediction through the XGBoost algorithm. [Conclusion] The value of the accuracy of patent prediction model reached 0.905. Among the combined features, the importance of market feature is the highest, and the importance of technical feature is the lowest. In the secondary index features, the feature of disclosed country is of the highest importance, and secondly, whether the entrusting agent and the patentee's geographical distribution are of higher importance in patent value prediction.

 

Sun, Ran (1); An, Lu (1,2)

1: Wuhan University, China, People's Republic of

2: Center for Studies of Information Resources, Wuhan University, China, People's Republic of

22/03/2021 06:00 +00:00 - 22/03/2021 07:30 +00:00
(22/03/2021 06:00 +00:00)
| Chinese Papers | 17 Attendees
Chinese Papers 4 (Chinese Papers)

(507) 认知视角下知识创造的知识元融合研究

Keywords: 知识元, 语义元, 知识创造, 融合, 认知

[目的/意义]知识创造是知识管理领域研究的热点问题。知识元的融合产生了创新知识元,是知识创造的根本原因。[方法/过程]我们探索了认知与知识元融合的关系,从知识元融合的层面揭示了知识创造的内部机理,构建了认知视角下知识创造的知识元融合模型。创新之处在于揭示了作为知识元融合核心的语义元结合范式,包括语义元结合的约束机制和认知运算机制。[结果/结论]实证结果表明,认知视角下知识创造的知识元融合模型从细粒度的、微观的层面揭示了知识元产生的融合机理,从根本上解释了知识创造的过程,为隐性知识的发现、关联、转化等知识管理问题提供了理论基础。

 

戎, 军涛 中国人民大学

China, People's Republic of

 

(509) 数字转型中的中国近现代史学者学术信息搜寻行为实证研究——基于Al-Suqri模型的考察

Keywords: 信息搜寻行为, 信息载体环境, Al-Suqri模型, 中国近现代史学者, 数字转型

[目的/意义]数字转型推动社会信息环境的快速转变,其中一个重要方面是电子载体信息资源越来越多,与传统的纸质信息资源并存。但不同载体环境下人文社科学者的学术信息搜寻行为尚未得到足够重视,需要进一步关注。[方法/过程]论文回顾国内外相关研究,以Al-Suqri提出的人文社科学者信息搜寻行为模型为基础,选取其中的“分类—筛选—选择资源—汇集信息”过程开展实证调研,对六名国内中青年中国近现代史学者进行访谈,采用定性分析法解读访谈结果,[结果/结论]总结两种不同载体环境下中青年近现代史学者学术信息搜寻行为的特征,提出面向图书馆、档案馆等正式信息源的学术信息搜寻细化过程。

 

Zhan, Yike; Chen, Xiyu

Sun Yat-sen University, China, People's Republic of

 

(512) A Study of Poets' Communication in Tang Dynasty Based on Social Network Analysis

Keywords: Tang Dynasty, Poet, Communication, Social network analysis

This paper discusses the changes of poets’ communication style in the Tang Dynasty by social network analysis method. Our research finds that poet’s communication style in different stages has different characteristics. Moreover, with the passage of time, the influence of political status declined.

 

Chen, Yuhang; Tang, Zhenyi; Wang, Rui; Ji, Jiawen

PeKing University, China, People's Republic of

22/03/2021 08:30 +00:00 - 22/03/2021 10:00 +00:00
(22/03/2021 08:30 +00:00)
| Full Research Papers | 46 Attendees
Full Research Papers 1 (Full Research Papers)
Kun Lu
Kun Lu
Associate Professor, University of Oklahoma SLIS
JC
Joyce Choi
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
CZ
Chenyang Zhang

(215) A Knowledge Representation Model for Studying Knowledge Creation, Usage, and Evolution

Keywords: Knowledge Representation Model, Knowledge Evolution, Full-text Citation Analysis, Alzheimer’s Disease

A knowledge representation model is proposed to facilitate studies on knowledge creation, usage, and evolution. The model uses a three-layer network structure to capture citation relationships among papers, the internal concept structure within individual papers, and the knowledge landscape in a domain. The resulting model can not only reveal the path and direction of knowledge diffusion, but also detail the content of knowledge transferred between papers, new knowledge added, and changing knowledge landscape in a domain. A pilot experiment is carried out using the PMC-OA dataset in the biomedical field. A case study on one knowledge evolution chain of Alzheimer’s Disease demonstrates the use of the model in revealing knowledge creation, usage, and evolution. Initial findings confirm the feasibility of the model for its purpose. Limitations of the study are discussed. Future work will try to address the recognized limitations and apply the model to large scale automated analysis to understand the knowledge production process.

 

Liang, Zhentao (1); Liu, Fei (1); Mao, Jin (1,2); Lu, Kun (3)

1: School of Information Management, Wuhan University, Wuhan, Hubei, China;

2: Center for Studies of Information Resources, Wuhan University, Wuhan, Hubei, China;

3: School of Library and Information Studies, University of Oklahoma, Norman OK 73019, USA

 

(270) Characterizing award-winning papers in library and information science: A case study of LIS journals published by Emerald

Keywords: Award-winning papers, LIS, Authorship, Paper type, Topic

This paper explores the characteristics of 106 award-winning papers from the Library and Information Science (LIS) journals published by Emerald Pub-lishing between 2008 and 2019, focusing on collaboration type, paper type, topic, and citation count to illustrate the developmental trends of LIS schol-arship. The findings show that the top three topics of the award-winning pa-pers were information service activities, professions and information institu-tions, and user studies. More than half of the award-winning papers were written by teams, among which inter-institutional collaboration and intrade-partmental collaboration accounted for the largest proportion, while interde-partmental collaboration within an institution accounted for the smallest proportion. There were 65 empirical research papers in the sample, among which qualitative studies were dominant, followed by quantitative research and mixed methods research. The award-winning papers had a higher mean and median in citation counts than the average papers concurrently pub-lished by the journals. The research results provide implications for research-ers and can help them understand the trends in research topics and common analytical types in LIS for their future studies.

 

Chen, Yi (1); Wang, Shengang (2); Yang, Li (2)

1: Wuhan University, China, People's Republic of;

2: University of Wisconsin–Milwaukee, USA

 

(314) Hybrid Research on Relevance Judgment and Eye Movement for Reverse Image Mobile Search

Keywords: Relevance Judgment, Reverse Image Mobile Search, SERP, Eye Movement

Relevance judgment has been studied in the information field for a long time. Eye movement data contains a large amount of user subjective infor-mation, and the way of its collection is becoming easier. With the rising penetration rate of mobile Internet, people are getting used to adopt the mo-bile search to solve problems. The higher the utilization rate of mobile search, the higher the user's requirements for the accuracy of mobile search results. In order to explore the user relevance judgment in the mobile re-verse image search scenario, this paper combines eye movement data to fig-ure out the relation between relevance judgment and users’ eye movement. With the help of the relation the user's relevance experience can be inferred through eye movement data, thereby optimizing the SERP page, so as to achieve the effect of reasonable search results ranking and recommendation accuracy.

 

Wu, Dan (1,2); Zhang, Chenyang (1); Ainiwaer, Abidan (1); Lv, Siyu (1)

1: School of Information Management, Wuhan University, China;

2: Center of Human-Computer Interaction and User Behavior, Wuhan University, China

22/03/2021 10:30 +00:00 - 22/03/2021 12:00 +00:00
(22/03/2021 10:30 +00:00)
| Full Research Papers | 33 Attendees
Full Research Papers 2 (Full Research Papers)
Anatoly Vasilievich Zolotaryuk
Anatoly Vasilievich Zolotaryuk
323, Financial University under the Government of the Russian Federation
TF
Tamás Fergencs
Master's Student, Aalborg University Copenhagen
Florian Meier
Florian Meier
Assistant Professor, Aalborg University Copenhagen
CR
Chamil Rathnayake
Lecturer, University of Strathclyde
Michael Seadle
Michael Seadle
Executive Director, iSchools Inc.
VO
Virginia Ortiz-Repiso
Proffesor, University Carlos III of Madrid

(323) Spatio-Temporal Deepfake Detection with Deep Neural Networks

Keywords: Generative Adversarial Networks, Deepfakes, Sliding Windows

Deepfakes generated by generative adversarial neural networks may threaten not only individuals but also pose a public threat. In this regard, detecting manipulations of video content is an urgent task, and many researchers propose various methods to solve it. Nevertheless, the problem remains. In this paper, the existing approaches are evaluated, and a new method for detecting deepfakes in videos is proposed. Considering that deepfakes are inserted into the video frame by frame, when viewing it, even with the naked eye, fluctuations and temporal distortions are noticeable, which are not taken into account by many deepfake detection algorithms that use information from a single frame to search for forgeries out of context with neighboring frames. It is proposed to analyze information from a sequence of multiple consecutive frames to detect deepfakes in video content by processing the video using the sliding window approach, taking into account not only spatial intraframe dependencies but also interframe temporal dependencies. Experiments have shown the advantage and potential for further development of the proposed approach over simple intraframe recognition.

 

Sebyakin, Andrey Sergeevich; Soloviev, Vladimir Igorevich; Zolotaryuk, Anatoly Vasilievich

Financial University under the Government of the Russian Federation, Russia

 

(244) Engagement and Usability of Conversational Search – A Study of a Medical Resource Center Chatbot

Keywords: Conversational search, search user interface, usability, user engagement, chatbot

Due to advances in natural language understanding, chatbots have become popular for assisting users in various tasks, for example, searching. Chatbots allow natural-language queries, which can be useful in case of complex information needs, and they provide a higher level of interactivity by displaying information in a dialog-like format. However, chatbots are often only used as auxiliaries for a graphical search user interface (SUI). Thus, they must be engaging and usable so that users both want to and are able to use them. In this study, we conduct a controlled interactive information retrieval experiment following a within-subject design to compare a chatbot to a graphical SUI in terms of engagement and usability. Our findings point towards the need for flawless usability in order for conversational search interfaces to (1) be able to provide additional value in information retrieval tasks and (2) elicit a higher level of engagement compared to their graphical SUI-based counterparts.

 

Fergencs, Tamás; Meier, Florian Aalborg

University Copenhagen, Denmark

 

(161) An Inquiry into Emotion Expression within Affective Publics on Twitter during the Covid-19 Emergency

Keywords: Sentiment Analysis, Affective Publics, Covid-19, Twitter, NHS

This study examines sentiments expressed in a dataset of 33,338 tweets that contain two hashtags–#NHSHeroes and #Covidiot–emerged in response to the global pandemic caused by Covid-19. The scope of the article is to discuss some methodological strategies useful to take advantage of sentiment analysis for social research purposes. Specifically, we suggest combining sentiment analysis with emotion detection, text analysis and social media engagement metrics in order to better understand the semantic and social context in which the sentiment related to a specific issue is situated. In this sense, we also contribute to affective publics literature, insofar we illustrate some techniques to quantitatively map fluxes of emotions structuring affective publics. Drawing on an exploration of the two affective publics aggregating around #NHSHeroes and #Covidiot, we argue that they reflect a blend of emotions. In some cases, such generic flow of affect coalesces into a dominant emotion while it may not necessarily occur in other instances. Affective publics structured around positive emotions and local issues tend to be more consistent and cohesive than those based on general issues and negative emotions. Although negative emotions might attract the attention of digital publics, positively framed messages engage users more. In the conclusion, we also stress how our methodology can help key stakeholders to design communication strategies to effectively cope with public concerns about Covid-19 in a post-pandemic scenario.

 

Rathnayake, Chamil (1); Caliandro, Alessandro (2)

1: University of Strathclyde, United Kingdom;

2: University of Pavia, Italy

22/03/2021 13:30 +00:00 - 22/03/2021 15:00 +00:00
(22/03/2021 13:30 +00:00)
| Full Research Papers | 48 Attendees
Full Research Papers 3 (Full Research Papers)
CA
Chulakorn Aritajati
Ph.D. Student, Pennsylvania State University
ZW
Zhendong Wang
PHD Student, University of Pittsburgh
YL
Yu Lu
PhD Student, Florida State University
TZ
Tara Zimmerman
Postdoctoral Research Fellow, University of Texas at Austin

(196) Smile! Positive Emojis Improve Reception and Intention to Use Constructive Feedback

Keywords: Computer-Mediated Communication\and Emoji\and Feedback\and Crowdsourcing\and Human-Computer Interaction

Feedback is essential to creative work. In fact, feedback is so valuable that online crowdwork platforms are sometimes used to gather it quickly and repeatedly. However, when feedback contains negative content, the receiver's mood may suffer, as well as his or her perceptions of the feedback and provider. In response, researchers have explored techniques to mitigate the negative impacts of constructive comments; surprisingly, few studies have investigated non-verbal communication such as images. We report an exploratory study of how the presence of positive emojis in a critique can affect the receivers' reactions. We found that the positive emojis increased receiver positivity, also decreasing annoyance and frustration. The emojis also evoked more positive perceptions of feedback providers, and increased intentions to apply the feedback to future work. We discuss implications for designing feedback platforms in ways that might encourage the addition of message-appropriate emojis.

 

Aritajati, Chulakorn; Rosson, Mary Beth

Pennsylvania State University, United States of America

 

(207) Characterizing Dementia Caregivers’ Information Exchange on Social Media: Exploring an Expert-Machine Co-Development Process

Keywords: Alzheimer’s disease and related dementias (ADRD) caregiving, Online information exchange, Expert-Machine Co-development (EMC), Interactive learning, Social media analysis

Social media platforms have introduced new opportunities for supporting family caregivers of persons with Alzheimer’s disease and related dementias (ADRD). Existing methods for exploring online information seeking and sharing (i.e., information exchange) involve examining online posts via manual analysis by human experts or fully automated data-driven exploration through text classification. Both methods have limitations. In this paper, we propose an innovative expert–machine co-development (EMC) process that enables rich interactions and co-learning between human experts and automatic algorithms. By applying the EMC in analyzing ADRD caregivers’ online behaviors, we illustrate steps required by the EMC, and demonstrate its effectiveness in enhancing human experts’ representations of ADRD caregivers’ online information exchange and developing more accurate automatic classification models for ADRD caregivers’ information exchange.

 

Wang, Zhendong (1); Zou, Ning (1); Xie, Bo (2); Luo, Zhimeng (1); He, Daqing (1); Hilsabeck, Robin C. (2); Aguirre, Alyssa (2)

1: University of Pittsburgh, United States of America;

2: University of Texas, United States of America

 

(303) Pregnancy-Related Information Seeking in Online Health Communities: A Qualitative Study

Keywords: Information Seeking, Needs Assessment, Consumer Health Information, Pregnant Women, Online Community

Pregnancy often imposes risks on women’s health. Women are increasingly turning to online resources (e.g., online health communities) to look for pregnancy-related information for better care management. To inform design opportunities for online support interventions, it is critical to thoroughly understand women’s information needs throughout pregnancy. In this study, we present a content analysis of pregnancy-related question posts on Yahoo! Answers to examine women’s information needs across the main stages of the pregnancy journey, how they formulated their inquiries, and the types of replies that information seekers received. This analysis revealed 14 main types of information needs, most of which were “stage-based”. We also found that peers from online health communities provided a variety of support, including affirmation of pregnancy, opinions or suggestions, health information, personal experience, and reference to health providers’ service. Insights derived from the findings are drawn to discuss design opportunities for tailoring informatics interventions to support women’s information needs at different pregnancy stages.

 

Lu, Yu (1); Zhang, Zhan (2); Min, Katherine (1); Luo, Xiao (3); He, Zhe (1)

1: Florida State University, United States of America;

2: Pace University, United States of America;

3: Indiana University–Purdue University Indianapolis, United States of America

22/03/2021 16:00 +00:00 - 22/03/2021 17:30 +00:00
(22/03/2021 16:00 +00:00)
| Plenary | 44 Attendees
(735) Georgia Tech’s online Master in Computer Science Program and the future of online learning (Plenary)

In March 2020, universities around the world were suddenly forced to move some or all of their teaching online. But Georgia Tech had begun the process six years earlier. In January 2014, Georgia Tech started the first MOOC-based online master in computer science program (OMSCS). OMSCS started with 380 students, but this spring the program enrolled 11,300 students — and it is still growing.

The talk will tell  the story of OMSCS: how it started, what we have learned and are still learning from it and the role it and its successors have played before and during the pandemic. It will also share some thoughts on the role online programs can play in the future of higher education.

 

Zvi Galil

Georgia Institute of Technology

22/03/2021 18:30 +00:00 - 22/03/2021 20:00 +00:00
(22/03/2021 18:30 +00:00)
| Short Research Papers | 40 Attendees
Short Research Papers 1 (Short Research Papers)
JD
Jennifer Douglas
Assistant Professor, University of British Columbia
HR
Hyeyoung Ryu
PhD student, University of Washington
SH
Seoyeon Hong
Yonsei University
Chris Holstrom
Chris Holstrom
University of Washington Information School
NV
Nitin Verma
Ph.D. Student, The University of Texas at Austin

(476) Is this too personal? An autoethnographic approach to researching intimate online archives

Keywords: Autoethnography, Personal research, Research ethics, Intimate online ar-chives

This short research paper uses a personal research story to explore how au-toethnographic methods can provide a guide to navigating the complicated ethics of researching online. Drawing on the author’s personal experience of bereavement and their subsequent research in online grief communities, the paper demonstrates how autoethnography can provide a lens for identifying points of tension, conflict and vulnerability in online research. The paper concludes by advocating for compassionate research and shows how au-toethnographic inquiry supports its development.

 

Douglas, Jennifer

University of British Columbia, Canada

 

(231) Appealing to the Gut Feeling: How Intermittent Fasters Choose Information Tab Interfaces for Information Acquisition

Keywords: Intermittent Fasting, Safety-Conscious Diet, Text Mining, Information Acquisition, Mobile Applications

Although many deem intermittent fasting (IF) a healthy dietary regimen, there is a paucity of scientific evidence to corroborate IF health benefits in human studies. However, its comparative ease and the emphasized benefits in the light of COVID-19 (e.g., weight loss and immunization improvement) have led to the increase of IF adoption. A vast number of intermittent fasters have not sought consultation from health professionals, which can bring adverse health effects. Most intermittent fasters use mobile apps to get assistance for IF. Types of assistance offered by the IF mobile applications may range from tracking (e.g., fasting periods, calorie intake) to obtaining knowledge about IF. However, it is unclear how much people are using the features for learning more about IF which is crucial to making healthier decisions in the IF adoption process. Thus, we organized our study into two stages for establishing design implications that further encourage a safety-conscious and user-friendly IF experience. We first investigated how IF app users who have chosen apps that provide extensive IF-specific knowledge acquire the said knowledge via (i) topic modeling of user app reviews, (ii) detecting modularity in co-word maps drawn from reviews specific to IF information acquisition, (iii) locating the position of keywords indicating information acquisition in the reviews. Then, we examined how users judge the effectiveness of knowledge provision interfaces in obtaining information. We investigated this aspect with an interface ranking user task for information tabs and organized user rationale using manual coding and co-word mapping.

 

Ryu, Hyeyoung (1); Hong, Seoyeon (2)

1: University of Washington, Seattle, WA;

2: Yonsei University, Seoul, Korea

 

(387) Studying Subject Ontogeny at Scale in a Polyhierarchical Indexing Language

Keywords: classification, subject ontogeny, large-scale indexing, polyhierarchy

Subject ontogeny, the study of how subjects change or do not change during revisions of indexing languages, has added to our understanding of indexing languages through case studies. However, subject ontogeny research to date has been unable to examine key functionality of indexing languages at scale. For example, how do large-scale changes to social and literary warrant affect the utility of indexing languages over time? This paper discusses concrete progress made towards studying subject ontogeny at scale and the challenges presented by studying a large-scale polyhierarchical indexing language, Wikipedia Categories. The paper presents early findings, argues for continued research on subject ontogeny at scale, and suggests possible paths forward for this research.

 

Holstrom, Chris; Tennis, Joseph T.

University of Washington Information School, United States of America

22/03/2021 21:00 +00:00 - 22/03/2021 22:30 +00:00
(22/03/2021 21:00 +00:00)
| Full Research Papers | 29 Attendees
Full Research Papers 4 (Full Research Papers)
VL
Valerie Lookingbill
Sciences Librarian, University of South Carolina
Douglas Zytko
Douglas Zytko
Assistant Professor, Oakland University
LX
Lu Xiao
Associate Professor, Syracuse University
KF
Katrina Fenlon
Assistant professor, University of Maryland, College Park

(276) “We can be our best alliance”: Resilient health information practices of LGBTQIA+ individuals as a buffering response to minority stress

Keywords: LGBTQ+, Information Practices, Minority Stress

This article examines the resilient information practices of lesbian, gay, bi-sexual, transgender, queer, intersex, and asexual (LGBTQIA+) individuals as agentic forms of buffering against minority stressors. Informed by semi-structured interviews with 30 LGBTQIA+ community leaders from a Southeastern state [removed for blind review], our findings demonstrate how LGBTQIA+ individuals engage in resilient health information practices and community-based resilience. Further, our findings also suggest that LGBTQIA+ communities integrate externally produced stressors. These findings have implications for future research on minority stress and resiliency strategies, such as shifting from outreach to engagement and leveraging what communities are doing, rather than assuming they are lacking. Further, as each identity and intersecting identities under the LGBTQIA+ umbrella has unique stressors and resilience strategies, our findings indicate how resilience strategies operate across each level of the socio-ecological model to better inform understanding of health information in context.

 

Lookingbill, Valerie; Vera, A. Nick; Wagner, Travis L.; Kitzie, Vanessa L.

University of South Carolina, United States of America

 

(328) Immersive Stories for Health Information: Design Considerations from Binge Drinking in VR

Keywords: Immersive stories, virtual reality, 360-degree video, film, public health

Immersive stories for health are 360° videos that intend to alter viewer perceptions about behaviors detrimental to health. They have potential to in-form public health at scale, however, immersive story design is still in early stages and largely devoid of best practices. This paper presents a focus group study with 147 viewers of an immersive story about binge drinking experienced through VR headsets and mobile phones. The objective of the study is to identify aspects of immersive story design that influence attitudes towards the health issue exhibited, and to understand how health in-formation is consumed in immersive stories. Findings emphasize the need for an immersive story to provide reasoning behind a character’s engagement in the focal health behavior, to show the main character clearly engaging in the behavior, and to enable viewers to experience escalating symptoms of the behavior before the penultimate health consequence. Findings also show how the design of supporting characters can inadvertently dis-tract viewers and lead them to justify the detrimental behavior being exhibited. The paper concludes with design considerations for enabling immersive stories to better inform public perception of health issues.

 

Zytko, Douglas; Ma, Zexin; Gleason, Jacob; Lundquist, Nathaniel; Taylor, Medina Oakland

University, United States of America

 

(353) Attracting Attention in Online Health Forums: Studies of r/Alzheimers and r/dementia

Keywords: Online Health Discussion, Attention, Dementia, Online Influence, Natural Language Processing

Informal caregivers increasingly use social media for means of information sharing and social support. We study the attention received by healthcare related social media posts, particularly the r/Alzheimers and r/dementia subreddits with the aim of better understanding the user experience on such forums, possibly leading to improvements of their effectiveness. We ex-plore how the linguistic features of a post relate to the amount of attention it receives in terms of votes and comments, focusing on the content, gram-mar, and sentiment of the text. Unlike traditional approaches that analyze forum activity on each user, we analyze each post as an entity to decipher what makes it influential. We do n-gram and word frequency analysis on the text to compare high- and low-attention posts, then define and calculate attention measures for each post before applying correlation analysis be-tween attention measures and post features. We perform topic modelling analysis on the posts and examine the correlation relationships between a post’s major topic and the amount of attention it receives. Our topic analy-sis of the posts, along with our n-gram and word frequency analysis, also infer themes of discussion within the subreddits.

 

Flynn, Olivia Aiden (1); Murugadass, Abinav (1); Xiao, Lu (2)

22/03/2021 23:30 +00:00 - 23/03/2021 01:00 +00:00
(22/03/2021 23:30 +00:00 - 23/03/2021 01:00 +00:00)
| Virtual Interactive Session (VIS) | 22 Attendees
(481) Just put it on Zoom!: Effectively Fostering a Virtual Intellectual Community Part 1 (Virtual Interactive Session (VIS))

Note: Participants need to be logged into a Zoom account to participate in this session!

 

Keywords: Virtual community, Zoom, digital tools, strategies

During a pandemic, the digital communities we create to maintain our social ties, to foster emotional well-being, and to feed our intellectual curiosity may be even further obscured. In this session, we offer our own experiences and invite playful sharing of software tools, events, and organizations that participants use to facilitate the development of their intellectual communities, foster emotional well-being, and maintain social ties. Guided by the principle of playfulness we will identify, record, and reflect on our experiences to help us recenter intellectual communities during a socially-distanced reality as well as to rethink the future. In the first session we will curate a list of experiences and resources to be followed by an active, playfully reflexive second session. Attendees can expect to contribute their experiences of digital tools , listen mindfully, and walk away with resources, tips, experiences to build their own virtual communities online.

 

Gursoy, Ayse; Shiroma, Kristina

University of Texas at Austin, United States of America

22/03/2021 16:00 +00:00 - 22/03/2021 17:30 +00:00
(22/03/2021 16:00 +00:00)
| Plenary | 44 Attendees
(735) Georgia Tech’s online Master in Computer Science Program and the future of online learning

In March 2020, universities around the world were suddenly forced to move some or all of their teaching online. But Georgia Tech had begun the process six years earlier. In January 2014, Georgia Tech started the first MOOC-based online master in computer science program (OMSCS). OMSCS started with 380 students, but this spring the program enrolled 11,300 students — and it is still growing.

The talk will tell  the story of OMSCS: how it started, what we have learned and are still learning from it and the role it and its successors have played before and during the pandemic. It will also share some thoughts on the role online programs can play in the future of higher education.

 

Zvi Galil

Georgia Institute of Technology

22/03/2021 08:30 +00:00 - 22/03/2021 10:00 +00:00
(22/03/2021 08:30 +00:00)
| Full Research Papers | 46 Attendees
Full Research Papers 1
Kun Lu
Kun Lu
Associate Professor, University of Oklahoma SLIS
JC
Joyce Choi
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
CZ
Chenyang Zhang

(215) A Knowledge Representation Model for Studying Knowledge Creation, Usage, and Evolution

Keywords: Knowledge Representation Model, Knowledge Evolution, Full-text Citation Analysis, Alzheimer’s Disease

A knowledge representation model is proposed to facilitate studies on knowledge creation, usage, and evolution. The model uses a three-layer network structure to capture citation relationships among papers, the internal concept structure within individual papers, and the knowledge landscape in a domain. The resulting model can not only reveal the path and direction of knowledge diffusion, but also detail the content of knowledge transferred between papers, new knowledge added, and changing knowledge landscape in a domain. A pilot experiment is carried out using the PMC-OA dataset in the biomedical field. A case study on one knowledge evolution chain of Alzheimer’s Disease demonstrates the use of the model in revealing knowledge creation, usage, and evolution. Initial findings confirm the feasibility of the model for its purpose. Limitations of the study are discussed. Future work will try to address the recognized limitations and apply the model to large scale automated analysis to understand the knowledge production process.

 

Liang, Zhentao (1); Liu, Fei (1); Mao, Jin (1,2); Lu, Kun (3)

1: School of Information Management, Wuhan University, Wuhan, Hubei, China;

2: Center for Studies of Information Resources, Wuhan University, Wuhan, Hubei, China;

3: School of Library and Information Studies, University of Oklahoma, Norman OK 73019, USA

 

(270) Characterizing award-winning papers in library and information science: A case study of LIS journals published by Emerald

Keywords: Award-winning papers, LIS, Authorship, Paper type, Topic

This paper explores the characteristics of 106 award-winning papers from the Library and Information Science (LIS) journals published by Emerald Pub-lishing between 2008 and 2019, focusing on collaboration type, paper type, topic, and citation count to illustrate the developmental trends of LIS schol-arship. The findings show that the top three topics of the award-winning pa-pers were information service activities, professions and information institu-tions, and user studies. More than half of the award-winning papers were written by teams, among which inter-institutional collaboration and intrade-partmental collaboration accounted for the largest proportion, while interde-partmental collaboration within an institution accounted for the smallest proportion. There were 65 empirical research papers in the sample, among which qualitative studies were dominant, followed by quantitative research and mixed methods research. The award-winning papers had a higher mean and median in citation counts than the average papers concurrently pub-lished by the journals. The research results provide implications for research-ers and can help them understand the trends in research topics and common analytical types in LIS for their future studies.

 

Chen, Yi (1); Wang, Shengang (2); Yang, Li (2)

1: Wuhan University, China, People's Republic of;

2: University of Wisconsin–Milwaukee, USA

 

(314) Hybrid Research on Relevance Judgment and Eye Movement for Reverse Image Mobile Search

Keywords: Relevance Judgment, Reverse Image Mobile Search, SERP, Eye Movement

Relevance judgment has been studied in the information field for a long time. Eye movement data contains a large amount of user subjective infor-mation, and the way of its collection is becoming easier. With the rising penetration rate of mobile Internet, people are getting used to adopt the mo-bile search to solve problems. The higher the utilization rate of mobile search, the higher the user's requirements for the accuracy of mobile search results. In order to explore the user relevance judgment in the mobile re-verse image search scenario, this paper combines eye movement data to fig-ure out the relation between relevance judgment and users’ eye movement. With the help of the relation the user's relevance experience can be inferred through eye movement data, thereby optimizing the SERP page, so as to achieve the effect of reasonable search results ranking and recommendation accuracy.

 

Wu, Dan (1,2); Zhang, Chenyang (1); Ainiwaer, Abidan (1); Lv, Siyu (1)

1: School of Information Management, Wuhan University, China;

2: Center of Human-Computer Interaction and User Behavior, Wuhan University, China

22/03/2021 10:30 +00:00 - 22/03/2021 12:00 +00:00
(22/03/2021 10:30 +00:00)
| Full Research Papers | 33 Attendees
Full Research Papers 2
Anatoly Vasilievich Zolotaryuk
Anatoly Vasilievich Zolotaryuk
323, Financial University under the Government of the Russian Federation
TF
Tamás Fergencs
Master's Student, Aalborg University Copenhagen
Florian Meier
Florian Meier
Assistant Professor, Aalborg University Copenhagen
CR
Chamil Rathnayake
Lecturer, University of Strathclyde
Michael Seadle
Michael Seadle
Executive Director, iSchools Inc.
VO
Virginia Ortiz-Repiso
Proffesor, University Carlos III of Madrid

(323) Spatio-Temporal Deepfake Detection with Deep Neural Networks

Keywords: Generative Adversarial Networks, Deepfakes, Sliding Windows

Deepfakes generated by generative adversarial neural networks may threaten not only individuals but also pose a public threat. In this regard, detecting manipulations of video content is an urgent task, and many researchers propose various methods to solve it. Nevertheless, the problem remains. In this paper, the existing approaches are evaluated, and a new method for detecting deepfakes in videos is proposed. Considering that deepfakes are inserted into the video frame by frame, when viewing it, even with the naked eye, fluctuations and temporal distortions are noticeable, which are not taken into account by many deepfake detection algorithms that use information from a single frame to search for forgeries out of context with neighboring frames. It is proposed to analyze information from a sequence of multiple consecutive frames to detect deepfakes in video content by processing the video using the sliding window approach, taking into account not only spatial intraframe dependencies but also interframe temporal dependencies. Experiments have shown the advantage and potential for further development of the proposed approach over simple intraframe recognition.

 

Sebyakin, Andrey Sergeevich; Soloviev, Vladimir Igorevich; Zolotaryuk, Anatoly Vasilievich

Financial University under the Government of the Russian Federation, Russia

 

(244) Engagement and Usability of Conversational Search – A Study of a Medical Resource Center Chatbot

Keywords: Conversational search, search user interface, usability, user engagement, chatbot

Due to advances in natural language understanding, chatbots have become popular for assisting users in various tasks, for example, searching. Chatbots allow natural-language queries, which can be useful in case of complex information needs, and they provide a higher level of interactivity by displaying information in a dialog-like format. However, chatbots are often only used as auxiliaries for a graphical search user interface (SUI). Thus, they must be engaging and usable so that users both want to and are able to use them. In this study, we conduct a controlled interactive information retrieval experiment following a within-subject design to compare a chatbot to a graphical SUI in terms of engagement and usability. Our findings point towards the need for flawless usability in order for conversational search interfaces to (1) be able to provide additional value in information retrieval tasks and (2) elicit a higher level of engagement compared to their graphical SUI-based counterparts.

 

Fergencs, Tamás; Meier, Florian Aalborg

University Copenhagen, Denmark

 

(161) An Inquiry into Emotion Expression within Affective Publics on Twitter during the Covid-19 Emergency

Keywords: Sentiment Analysis, Affective Publics, Covid-19, Twitter, NHS

This study examines sentiments expressed in a dataset of 33,338 tweets that contain two hashtags–#NHSHeroes and #Covidiot–emerged in response to the global pandemic caused by Covid-19. The scope of the article is to discuss some methodological strategies useful to take advantage of sentiment analysis for social research purposes. Specifically, we suggest combining sentiment analysis with emotion detection, text analysis and social media engagement metrics in order to better understand the semantic and social context in which the sentiment related to a specific issue is situated. In this sense, we also contribute to affective publics literature, insofar we illustrate some techniques to quantitatively map fluxes of emotions structuring affective publics. Drawing on an exploration of the two affective publics aggregating around #NHSHeroes and #Covidiot, we argue that they reflect a blend of emotions. In some cases, such generic flow of affect coalesces into a dominant emotion while it may not necessarily occur in other instances. Affective publics structured around positive emotions and local issues tend to be more consistent and cohesive than those based on general issues and negative emotions. Although negative emotions might attract the attention of digital publics, positively framed messages engage users more. In the conclusion, we also stress how our methodology can help key stakeholders to design communication strategies to effectively cope with public concerns about Covid-19 in a post-pandemic scenario.

 

Rathnayake, Chamil (1); Caliandro, Alessandro (2)

1: University of Strathclyde, United Kingdom;

2: University of Pavia, Italy

22/03/2021 13:30 +00:00 - 22/03/2021 15:00 +00:00
(22/03/2021 13:30 +00:00)
| Full Research Papers | 48 Attendees
Full Research Papers 3
CA
Chulakorn Aritajati
Ph.D. Student, Pennsylvania State University
ZW
Zhendong Wang
PHD Student, University of Pittsburgh
YL
Yu Lu
PhD Student, Florida State University
TZ
Tara Zimmerman
Postdoctoral Research Fellow, University of Texas at Austin

(196) Smile! Positive Emojis Improve Reception and Intention to Use Constructive Feedback

Keywords: Computer-Mediated Communication\and Emoji\and Feedback\and Crowdsourcing\and Human-Computer Interaction

Feedback is essential to creative work. In fact, feedback is so valuable that online crowdwork platforms are sometimes used to gather it quickly and repeatedly. However, when feedback contains negative content, the receiver's mood may suffer, as well as his or her perceptions of the feedback and provider. In response, researchers have explored techniques to mitigate the negative impacts of constructive comments; surprisingly, few studies have investigated non-verbal communication such as images. We report an exploratory study of how the presence of positive emojis in a critique can affect the receivers' reactions. We found that the positive emojis increased receiver positivity, also decreasing annoyance and frustration. The emojis also evoked more positive perceptions of feedback providers, and increased intentions to apply the feedback to future work. We discuss implications for designing feedback platforms in ways that might encourage the addition of message-appropriate emojis.

 

Aritajati, Chulakorn; Rosson, Mary Beth

Pennsylvania State University, United States of America

 

(207) Characterizing Dementia Caregivers’ Information Exchange on Social Media: Exploring an Expert-Machine Co-Development Process

Keywords: Alzheimer’s disease and related dementias (ADRD) caregiving, Online information exchange, Expert-Machine Co-development (EMC), Interactive learning, Social media analysis

Social media platforms have introduced new opportunities for supporting family caregivers of persons with Alzheimer’s disease and related dementias (ADRD). Existing methods for exploring online information seeking and sharing (i.e., information exchange) involve examining online posts via manual analysis by human experts or fully automated data-driven exploration through text classification. Both methods have limitations. In this paper, we propose an innovative expert–machine co-development (EMC) process that enables rich interactions and co-learning between human experts and automatic algorithms. By applying the EMC in analyzing ADRD caregivers’ online behaviors, we illustrate steps required by the EMC, and demonstrate its effectiveness in enhancing human experts’ representations of ADRD caregivers’ online information exchange and developing more accurate automatic classification models for ADRD caregivers’ information exchange.

 

Wang, Zhendong (1); Zou, Ning (1); Xie, Bo (2); Luo, Zhimeng (1); He, Daqing (1); Hilsabeck, Robin C. (2); Aguirre, Alyssa (2)

1: University of Pittsburgh, United States of America;

2: University of Texas, United States of America

 

(303) Pregnancy-Related Information Seeking in Online Health Communities: A Qualitative Study

Keywords: Information Seeking, Needs Assessment, Consumer Health Information, Pregnant Women, Online Community

Pregnancy often imposes risks on women’s health. Women are increasingly turning to online resources (e.g., online health communities) to look for pregnancy-related information for better care management. To inform design opportunities for online support interventions, it is critical to thoroughly understand women’s information needs throughout pregnancy. In this study, we present a content analysis of pregnancy-related question posts on Yahoo! Answers to examine women’s information needs across the main stages of the pregnancy journey, how they formulated their inquiries, and the types of replies that information seekers received. This analysis revealed 14 main types of information needs, most of which were “stage-based”. We also found that peers from online health communities provided a variety of support, including affirmation of pregnancy, opinions or suggestions, health information, personal experience, and reference to health providers’ service. Insights derived from the findings are drawn to discuss design opportunities for tailoring informatics interventions to support women’s information needs at different pregnancy stages.

 

Lu, Yu (1); Zhang, Zhan (2); Min, Katherine (1); Luo, Xiao (3); He, Zhe (1)

1: Florida State University, United States of America;

2: Pace University, United States of America;

3: Indiana University–Purdue University Indianapolis, United States of America

22/03/2021 21:00 +00:00 - 22/03/2021 22:30 +00:00
(22/03/2021 21:00 +00:00)
| Full Research Papers | 29 Attendees
Full Research Papers 4
VL
Valerie Lookingbill
Sciences Librarian, University of South Carolina
Douglas Zytko
Douglas Zytko
Assistant Professor, Oakland University
LX
Lu Xiao
Associate Professor, Syracuse University
KF
Katrina Fenlon
Assistant professor, University of Maryland, College Park

(276) “We can be our best alliance”: Resilient health information practices of LGBTQIA+ individuals as a buffering response to minority stress

Keywords: LGBTQ+, Information Practices, Minority Stress

This article examines the resilient information practices of lesbian, gay, bi-sexual, transgender, queer, intersex, and asexual (LGBTQIA+) individuals as agentic forms of buffering against minority stressors. Informed by semi-structured interviews with 30 LGBTQIA+ community leaders from a Southeastern state [removed for blind review], our findings demonstrate how LGBTQIA+ individuals engage in resilient health information practices and community-based resilience. Further, our findings also suggest that LGBTQIA+ communities integrate externally produced stressors. These findings have implications for future research on minority stress and resiliency strategies, such as shifting from outreach to engagement and leveraging what communities are doing, rather than assuming they are lacking. Further, as each identity and intersecting identities under the LGBTQIA+ umbrella has unique stressors and resilience strategies, our findings indicate how resilience strategies operate across each level of the socio-ecological model to better inform understanding of health information in context.

 

Lookingbill, Valerie; Vera, A. Nick; Wagner, Travis L.; Kitzie, Vanessa L.

University of South Carolina, United States of America

 

(328) Immersive Stories for Health Information: Design Considerations from Binge Drinking in VR

Keywords: Immersive stories, virtual reality, 360-degree video, film, public health

Immersive stories for health are 360° videos that intend to alter viewer perceptions about behaviors detrimental to health. They have potential to in-form public health at scale, however, immersive story design is still in early stages and largely devoid of best practices. This paper presents a focus group study with 147 viewers of an immersive story about binge drinking experienced through VR headsets and mobile phones. The objective of the study is to identify aspects of immersive story design that influence attitudes towards the health issue exhibited, and to understand how health in-formation is consumed in immersive stories. Findings emphasize the need for an immersive story to provide reasoning behind a character’s engagement in the focal health behavior, to show the main character clearly engaging in the behavior, and to enable viewers to experience escalating symptoms of the behavior before the penultimate health consequence. Findings also show how the design of supporting characters can inadvertently dis-tract viewers and lead them to justify the detrimental behavior being exhibited. The paper concludes with design considerations for enabling immersive stories to better inform public perception of health issues.

 

Zytko, Douglas; Ma, Zexin; Gleason, Jacob; Lundquist, Nathaniel; Taylor, Medina Oakland

University, United States of America

 

(353) Attracting Attention in Online Health Forums: Studies of r/Alzheimers and r/dementia

Keywords: Online Health Discussion, Attention, Dementia, Online Influence, Natural Language Processing

Informal caregivers increasingly use social media for means of information sharing and social support. We study the attention received by healthcare related social media posts, particularly the r/Alzheimers and r/dementia subreddits with the aim of better understanding the user experience on such forums, possibly leading to improvements of their effectiveness. We ex-plore how the linguistic features of a post relate to the amount of attention it receives in terms of votes and comments, focusing on the content, gram-mar, and sentiment of the text. Unlike traditional approaches that analyze forum activity on each user, we analyze each post as an entity to decipher what makes it influential. We do n-gram and word frequency analysis on the text to compare high- and low-attention posts, then define and calculate attention measures for each post before applying correlation analysis be-tween attention measures and post features. We perform topic modelling analysis on the posts and examine the correlation relationships between a post’s major topic and the amount of attention it receives. Our topic analy-sis of the posts, along with our n-gram and word frequency analysis, also infer themes of discussion within the subreddits.

 

Flynn, Olivia Aiden (1); Murugadass, Abinav (1); Xiao, Lu (2)

22/03/2021 18:30 +00:00 - 22/03/2021 20:00 +00:00
(22/03/2021 18:30 +00:00)
| Short Research Papers | 40 Attendees
Short Research Papers 1
JD
Jennifer Douglas
Assistant Professor, University of British Columbia
HR
Hyeyoung Ryu
PhD student, University of Washington
SH
Seoyeon Hong
Yonsei University
Chris Holstrom
Chris Holstrom
University of Washington Information School
NV
Nitin Verma
Ph.D. Student, The University of Texas at Austin

(476) Is this too personal? An autoethnographic approach to researching intimate online archives

Keywords: Autoethnography, Personal research, Research ethics, Intimate online ar-chives

This short research paper uses a personal research story to explore how au-toethnographic methods can provide a guide to navigating the complicated ethics of researching online. Drawing on the author’s personal experience of bereavement and their subsequent research in online grief communities, the paper demonstrates how autoethnography can provide a lens for identifying points of tension, conflict and vulnerability in online research. The paper concludes by advocating for compassionate research and shows how au-toethnographic inquiry supports its development.

 

Douglas, Jennifer

University of British Columbia, Canada

 

(231) Appealing to the Gut Feeling: How Intermittent Fasters Choose Information Tab Interfaces for Information Acquisition

Keywords: Intermittent Fasting, Safety-Conscious Diet, Text Mining, Information Acquisition, Mobile Applications

Although many deem intermittent fasting (IF) a healthy dietary regimen, there is a paucity of scientific evidence to corroborate IF health benefits in human studies. However, its comparative ease and the emphasized benefits in the light of COVID-19 (e.g., weight loss and immunization improvement) have led to the increase of IF adoption. A vast number of intermittent fasters have not sought consultation from health professionals, which can bring adverse health effects. Most intermittent fasters use mobile apps to get assistance for IF. Types of assistance offered by the IF mobile applications may range from tracking (e.g., fasting periods, calorie intake) to obtaining knowledge about IF. However, it is unclear how much people are using the features for learning more about IF which is crucial to making healthier decisions in the IF adoption process. Thus, we organized our study into two stages for establishing design implications that further encourage a safety-conscious and user-friendly IF experience. We first investigated how IF app users who have chosen apps that provide extensive IF-specific knowledge acquire the said knowledge via (i) topic modeling of user app reviews, (ii) detecting modularity in co-word maps drawn from reviews specific to IF information acquisition, (iii) locating the position of keywords indicating information acquisition in the reviews. Then, we examined how users judge the effectiveness of knowledge provision interfaces in obtaining information. We investigated this aspect with an interface ranking user task for information tabs and organized user rationale using manual coding and co-word mapping.

 

Ryu, Hyeyoung (1); Hong, Seoyeon (2)

1: University of Washington, Seattle, WA;

2: Yonsei University, Seoul, Korea

 

(387) Studying Subject Ontogeny at Scale in a Polyhierarchical Indexing Language

Keywords: classification, subject ontogeny, large-scale indexing, polyhierarchy

Subject ontogeny, the study of how subjects change or do not change during revisions of indexing languages, has added to our understanding of indexing languages through case studies. However, subject ontogeny research to date has been unable to examine key functionality of indexing languages at scale. For example, how do large-scale changes to social and literary warrant affect the utility of indexing languages over time? This paper discusses concrete progress made towards studying subject ontogeny at scale and the challenges presented by studying a large-scale polyhierarchical indexing language, Wikipedia Categories. The paper presents early findings, argues for continued research on subject ontogeny at scale, and suggests possible paths forward for this research.

 

Holstrom, Chris; Tennis, Joseph T.

University of Washington Information School, United States of America

22/03/2021 01:00 +00:00 - 22/03/2021 02:30 +00:00
(22/03/2021 01:00 +00:00)
| Chinese Papers | 33 Attendees
Chinese Papers 2

(590) 国外档案学学科建设与发展领域分析及启示 ——基于对55所院校的调查

Keywords: 国外档案学, 学科建设, 发展领域, 学科独立性, 中国特色档案学

跟踪了解国外档案学学科建设和发展的最新动向,可以为我国档案学学科建设和发展提供参考和洞见。本研究对国外55所重点院校档案学专业的学科点设置、学位设置和重点发展领域进行了调研分析。研究发现,国外档案学学科建设与发展具有注重学科融合发展、以职业教育为重要导向、学科独立性较弱和开阔的档案社会化研究视野等特征。基于此,提出我国档案学学科建设发展的建议:加强学科融合发展,强化综合能力培养;重视职业导向教育,打造多元融合的人才培养体系;保持学科独立性,发展中国特色档案学教育;关注社会视角下的档案事业发展,增添人文关怀。

 

Wang, Ning; Li, Mengqiu

Renmin University of China, China, People's Republic of China

 

(524) 多元融合视域下学术期刊话语权评价研究——以中国英文学术期刊为例

Keywords: 学术期刊;话语权评价;话语影响力;话语引导力;科学计量学;Altmetrics

本文基于评价科学理论、话语权理论和传播学理论,首先探讨了学术期刊话语权评价的基本问题:界定了学术话语权和学术期刊话语权等概念内涵;提出了学术期刊话语权由话语影响力和话语引导力维度构成,话语影响力由话语影响能力和话语影响权力要素组成,话语引导力由新闻话语、社交媒体话语、同行评议话语、百科话语、视频话语以及政策话语引导等要素组成;探究了学术期刊话语权形成过程和运作机理;构建了中国英文学术期刊话语权评价模型;其次融合多源异构数据,采用相关分析、集成因子分析、熵权法、TOPSIS法以及二维映射法优势,从多维度、多要素、多指标、多方法融合、比较和评估视角进行了中国英文学术期刊话语权评价实证研究。结果表明,本文按照理论、方法与应用逻辑展开多元融合的学术期刊话语权评价研究具有一定的实用性、兼顾性和可靠性。本文旨在为我国学术期刊话语权评价和管理决策、创建世界一流学术期刊,进而提升中国学术期刊话语权提供参考。

 

Wang, Xu

School of Economics and Management, Yanshan University, China, People's Republic of

 

(542) 结合巴斯扩散模型及SIR模型的微信公众号内容传播特征分析

Keywords: 微信公众号, 信息传播, 巴斯扩散模型, SIR模型

微信公众号内容的传播包括两条扩散路径:公众号直接将信息推送给其订阅用户产生首轮的传播以及非公众号订阅用户通过其它用户的转发与传播接触信息。本研究通过对微信公众号内容传播过程的分析,提出了结合巴斯扩散模型和SIR传染病模型的公众号传播模型,用以揭示其内容的传播规律。本研究利用“图情会”公众号阅读数据对模型进行KS检验,结果显示,模型总体上能够对公众号内容的传播过程进行模拟。研究通过对模型中参数及模型初始条件进行分析发现,已分享过的读者不再进行分享的概率,以及非公众号订阅用户从其它人转发中接触到信息的概率对公众号内容在目标群体中的扩散范围有较大影响;高阅读量的公众号内容往往在内容上有“破圈”的特性,往往能吸引到更多非订阅用户进行阅读,具有更广的传播范围。

 

Yang, SiLuo; Xiao, AoXia

School of Information Management, Wuhan University, China

22/03/2021 03:30 +00:00 - 22/03/2021 05:00 +00:00
(22/03/2021 03:30 +00:00)
| Chinese Papers | 24 Attendees
Chinese Papers 3

(513) A components framework conception for big data governance rules

Keywords: big data governance; big data governance rules; the components framework for rules

This research clarifies the relevant concepts of big data governance rules and proposes the framework of the components of big data governance rules, which aims to provide reference for the research of big data governance rules and guidance for the practice of big data governance. [Method/process] Using the method of literature survey, this paper reviews the existing relevant research, combs the relevant disciplines and governance rules, studies the components of big data governance rules and the relationship between them, and uses the methods of policy analysis and case study to map and verify the components of big data governance rules in national policies. [Result/conclusion] From the perspective of theoretical basis and analysis, this paper puts forward 15 components of big data governance rules including governance benefit components from four mapping dimensions and discusses the relationship between different components and the direction of future research and practice.

 

Jie, Huang

Renmin University of China, China, People's Republic of

 

(556) The current situation, problems and Countermeasures of Digital Humanities Education in China from the perspective of students

Keywords: Digital Humanities Education; Digital Humanities; Talent Training; The Perspective of Students

This paper describes the current situation of digital humanities education in China, reveals problems and proposes corresponding solutions from the perspective of students, aiming to provide enlightenment and reference for digital humanities education practice.

Design/methodology/approach - Taking the digital humanities education practice of Renmin University of China as a case, this paper uses code analysis to process data.

Findings - In the current digital humanities education, there are two different demands and training goals of "humanities who understand technology" and "technical experts who understand humanities"; there is a significant information asymmetry between education providers and students; the humanistic characteristics are outstanding but the technology is still weak; the project-based teaching has achieved good results, but the substantive guidance and assistance from the education provider is relatively less; the interdisciplinary communication and cooperation of the student project team are facing many challenges and the students lack effective feedback channels.

Original value - This paper describes the current situation of digital humanities education in China, reveals problems and proposes corresponding solutions from the perspective of student

 

He, Siyuan; Zhang, Chenwen; Ga, Lasen; Pei, Junliang

Renmin; University of China

 

(575) Research on the prediction of 5G patent value at home and abroad

Keywords: patent value, 5G, technology life cycle, XGBoost; prediction

This study aims to build a patent value evaluation system, and prospectively predict high-value patents. [Design/Methodology] Based on the patent data related to 5G technology in the Incopat patent database, we comprehensively considered the internal and external factors of the value of 5G patents, and used the Logistic model to visualize the technology life cycle of 5G patents at home and abroad. We built a patent value prediction model that includes patented technical features, market features, legal features, and patentee features. We used random forest, decision tree and XGBoost algorithm for training and evaluation. Finally, we tuned the model parameters and calculated the importance of different features in patent value prediction through the XGBoost algorithm. [Conclusion] The value of the accuracy of patent prediction model reached 0.905. Among the combined features, the importance of market feature is the highest, and the importance of technical feature is the lowest. In the secondary index features, the feature of disclosed country is of the highest importance, and secondly, whether the entrusting agent and the patentee's geographical distribution are of higher importance in patent value prediction.

 

Sun, Ran (1); An, Lu (1,2)

1: Wuhan University, China, People's Republic of

2: Center for Studies of Information Resources, Wuhan University, China, People's Republic of

22/03/2021 06:00 +00:00 - 22/03/2021 07:30 +00:00
(22/03/2021 06:00 +00:00)
| Chinese Papers | 17 Attendees
Chinese Papers 4

(507) 认知视角下知识创造的知识元融合研究

Keywords: 知识元, 语义元, 知识创造, 融合, 认知

[目的/意义]知识创造是知识管理领域研究的热点问题。知识元的融合产生了创新知识元,是知识创造的根本原因。[方法/过程]我们探索了认知与知识元融合的关系,从知识元融合的层面揭示了知识创造的内部机理,构建了认知视角下知识创造的知识元融合模型。创新之处在于揭示了作为知识元融合核心的语义元结合范式,包括语义元结合的约束机制和认知运算机制。[结果/结论]实证结果表明,认知视角下知识创造的知识元融合模型从细粒度的、微观的层面揭示了知识元产生的融合机理,从根本上解释了知识创造的过程,为隐性知识的发现、关联、转化等知识管理问题提供了理论基础。

 

戎, 军涛 中国人民大学

China, People's Republic of

 

(509) 数字转型中的中国近现代史学者学术信息搜寻行为实证研究——基于Al-Suqri模型的考察

Keywords: 信息搜寻行为, 信息载体环境, Al-Suqri模型, 中国近现代史学者, 数字转型

[目的/意义]数字转型推动社会信息环境的快速转变,其中一个重要方面是电子载体信息资源越来越多,与传统的纸质信息资源并存。但不同载体环境下人文社科学者的学术信息搜寻行为尚未得到足够重视,需要进一步关注。[方法/过程]论文回顾国内外相关研究,以Al-Suqri提出的人文社科学者信息搜寻行为模型为基础,选取其中的“分类—筛选—选择资源—汇集信息”过程开展实证调研,对六名国内中青年中国近现代史学者进行访谈,采用定性分析法解读访谈结果,[结果/结论]总结两种不同载体环境下中青年近现代史学者学术信息搜寻行为的特征,提出面向图书馆、档案馆等正式信息源的学术信息搜寻细化过程。

 

Zhan, Yike; Chen, Xiyu

Sun Yat-sen University, China, People's Republic of

 

(512) A Study of Poets' Communication in Tang Dynasty Based on Social Network Analysis

Keywords: Tang Dynasty, Poet, Communication, Social network analysis

This paper discusses the changes of poets’ communication style in the Tang Dynasty by social network analysis method. Our research finds that poet’s communication style in different stages has different characteristics. Moreover, with the passage of time, the influence of political status declined.

 

Chen, Yuhang; Tang, Zhenyi; Wang, Rui; Ji, Jiawen

PeKing University, China, People's Republic of

22/03/2021 23:30 +00:00 - 23/03/2021 01:00 +00:00
(22/03/2021 23:30 +00:00 - 23/03/2021 01:00 +00:00)
| Virtual Interactive Session (VIS) | 22 Attendees
(481) Just put it on Zoom!: Effectively Fostering a Virtual Intellectual Community Part 1

Note: Participants need to be logged into a Zoom account to participate in this session!

 

Keywords: Virtual community, Zoom, digital tools, strategies

During a pandemic, the digital communities we create to maintain our social ties, to foster emotional well-being, and to feed our intellectual curiosity may be even further obscured. In this session, we offer our own experiences and invite playful sharing of software tools, events, and organizations that participants use to facilitate the development of their intellectual communities, foster emotional well-being, and maintain social ties. Guided by the principle of playfulness we will identify, record, and reflect on our experiences to help us recenter intellectual communities during a socially-distanced reality as well as to rethink the future. In the first session we will curate a list of experiences and resources to be followed by an active, playfully reflexive second session. Attendees can expect to contribute their experiences of digital tools , listen mindfully, and walk away with resources, tips, experiences to build their own virtual communities online.

 

Gursoy, Ayse; Shiroma, Kristina

University of Texas at Austin, United States of America

Plenary
(736) Data Feminism
Full Research Papers
Full Research Papers 5
Short Research Papers
Short Research Papers 2
Short Research Papers 3
Short Research Papers 4
Short Research Papers 5
Short Research Papers 6
Short Research Papers 7
Special Presentations
(737) Curriculum Committee Reports: Data Science & Digital Humanities
Overall
Plenary
Full Research Papers
Short Research Papers
Special Presentations
All Events
# Gamification
# News
23/03/2021 00:00 +00:00 - 23/03/2021 01:30 +00:00
(23/03/2021 00:00 +00:00)
| Short Research Papers | 33 Attendees
Short Research Papers 2 (Short Research Papers)

(320) Becoming open knowledge institutions: divergence, dialogue and diversity

Keywords: Open Knowledge Institutions, Open Access performance, Higher education, Data visualization

The Curtin Open Knowledge Initiative (COKI) is an innovative research project that collects and analyses publicly available research output data to assist and encourage re-searchers, academics, administrators and executives to understand the actual and potential reach of openness in research, and to assess their progress on the path towards open knowledge institutions. By taking a broad global approach and using multiple data sources, the project diverges from existing approaches, methods and bibliometric measures in the scholarly research environment. It combines analysis of research output, citations, publication sources and publishers, funders, and social media events, open and not open access to provide overviews of research output and performance at institutional, funder, consortial and country levels. The project collects and analyses personnel diversity data such as gender and origin, focusing on widening the reach of data analysis to emphasise the importance and value of diversity in research and knowledge production. Interactive visual tools present research output and performance to encourage understanding and dialogue among researchers and managers. The path towards becoming open knowledge institutions involves a process of cultural change, moving beyond dominant publishing practices. This paper discusses how through divergence, diversity and dialogue the COKI project can contribute to this change, with examples of data use in understanding and embracing openness.

 

Wilson, Katie (1); Montgomery, Lucy (1); Neylon, Cameron (1); Handcock, Rebecca N. (2); Hosking, Richard (2); Huang, Chun-Kai {Karl} (1); Ozaygen, Alkim (1); Roelofs, Aniek (2)

1: Centre for Culture and Technology, Curtin University, Australia

2: Curtin Institute for Computation, Curtin University, Australia

 

(199) Aggregation and Utilization of Metadata for Intangible Folk Cultural Properties Using Linked Open Data

Keywords: Intangible Folk Cultural Properties, Metadata, Linked Open Data, CIDOC CRM, SPARQL

Intangible Folk Cultural Properties (IFCP) represent cultural customs or events related to transition in people's lives, and need to be protected and passed on to future generations. The Japanese government adopted the revised Act on Protection of Cultural Properties in 2018, which aims to ensure comprehensive protection and utilization of cultural properties. IFCP are required to make it available and accessible to the public considering these features. This study proposes an IFCP data model using Linked Open Data (LOD). This model is based on the CIDOC Conceptual Reference Model (CRM) and other vocabularies. We constructed a dataset based on this model and published it on the web. The dataset contains 5,106 triples from 103 IFCP focusing on religious faiths festivals (RF) and annual observances (AO). To evaluate our data model, we defined functional requirements for the IFCP and implemented a prototype system to verify utilization feasibility of the IFCP. The prototype system shows the IFCP lists based on retrieval feature using the SPARQL query language.

 

Sato, Itsumi; Takaku, Masao

University of Tsukuba, Japan

 

(342) Research on the Decision-making Process of Public Personnel Resisting Open Data Motivated by Perceived Risks

Based on the cognition of stakeholders, this paper reveals the decision-making process of civil servants resisting open data based on perceived risks. Adopting grounded theory, this study interviewed 22 stakeholders to collect data and then identified four factors as the pillars of the theoretical framework: perception of risks, conservative organizational culture, insufficient external pressure and poor operability. After that, this paper constructed a model for the decision path, which explains the formation of perceived risks of civil servants, and it al-so explains how the perceived risks are transformed into resistance motivation and make a behavior decision. Based on the level of certainty, the decision envi-ronment can be divided into the resistance decision path under the determined environment and that under the uncertain environment. This study also summa-rizes that accountability and loss of interest are two types of risk that can be considered when civil servants decide not to open data.

 

Li, Si (1); Chen, Yi (2)

1: Peking University

2: Wuhan University

23/03/2021 02:30 +00:00 - 23/03/2021 04:00 +00:00
(23/03/2021 02:30 +00:00)
| Special Presentations | 65 Attendees
(737) Curriculum Committee Reports: Data Science & Digital Humanities (Special Presentations)
Sam Oh.
Sam Oh.
Professor, Sungkyunkwan University
John Anthony Walsh
John Anthony Walsh
Associate Professor, Indiana University
IS
IL-YEOL SONG
Professor, Drexel University
JM
Javed Mostafa
Professor & Director, The University of North Carolina at Chapel Hill
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
LH
Loni Hagen
Assistant Professor, University of South Florida
Simon Mahony
Simon Mahony
Professor, Beijing Normal University at Zhuhai
MARCIA ZENG
MARCIA ZENG
Professor, Kent State University

The iSchools established two curriculum committees to find a unique iSchool approach to data science and to examine what contributions iSchools can make in the emerging discipline of digital humanities. The two committees were composed of experts from the entire iSchools network and investigated diverse aspects of the charge at hand for 2 years. This session will report the results of intense research and suggest a way forward for iSchools.

23/03/2021 05:00 +00:00 - 23/03/2021 06:00 +00:00
(23/03/2021 05:00 +00:00)
| Short Research Papers | 28 Attendees
Short Research Papers 3 (Short Research Papers)

(264) A Meta-Review of Gamification Research

Keywords: Gamification, Gamification Review, Meta-Review

Gamification has gained significant attention from academia and industry in the recent decade. Correspondingly, there has been a prolific publication rec-ord on gamification research. This research aims to explore a landscape view of gamification research through a meta-review, a systematical assessment of a collection of gamification literature reviews. The meta-review addresses four research questions on (1) literature review scope, (2) application do-mains, (3) review types, and (4) review foci in 48 reviews published from January 2018 to June 2020. This research contributes to a high-level over-view of the state of development in the gamification field. It also demon-strates a process of conducting meta-reviews.

 

Zhang, Ping (1); Tang, Jian (2); Jeong, Eunmi{Ellie} (1)

1: Syracuse University, USA

2: Central University of Finance and Economics, China

 

(293) A pilot ethnographic study of gamified English learning among Primary Four and Five students in a rural Chinese primary school

Keywords: Gamification, English reading literacy, self-determination theory, rural school

This pilot ethnographic study examines the feasibility of learning English with a gamified English e-learning platform among Primary Four (P4) and Primary Five (P5) students in a remote primary school in Henan, China. Forty-one students participated in a summer reading camp where the gamified platform in question was used. Results show that following 4 weeks of playing on the gamified platform, the majority of students developed substantial interest in reading more English books upon the fulfillment of their innate psychological needs for competence, relatedness and autonomy. The authors conclude that under a self-determination framework, the gamified platform has been effective in helping Chinese students in a rural community to learn English.

 

Meng, Na (1); Lee, Cameron S.Y. (2); Chu, Samuel K.W. (2)

1: Jinling Institute of Technology, Nanjing, China

2: Faculty of Education, the University of Hong Kong, Hong Kong, China

23/03/2021 09:30 +00:00 - 23/03/2021 11:00 +00:00
(23/03/2021 09:30 +00:00)
| Short Research Papers | 24 Attendees
Short Research Papers 4 (Short Research Papers)
Anastasia Zhukova
Anastasia Zhukova
Doctoral Researcher, University of Wuppertal
Timo Michael Spinde
Timo Michael Spinde
Ph.D., University of Wuppertal
Felix Hamborg
Felix Hamborg
Doctoral Researcher, University of Konstanz
TB
Toine Bogers
Asssociate professor, Aalborg University Copenhagen

(208) Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons

Keywords: concept identification, news analysis, clustering, media bias

Unsupervised concept identification through clustering, i.e., identification of semantically related words and phrases, is a common approach to identify contextual primitives employed in various use cases, e.g., text dimension reduction, i.e., replace words with the concepts to reduce the vocabulary size, summarization, and named entity resolution. We demonstrate the first results of an unsupervised approach for the identification of groups of persons as actors extracted from a set of related articles. Specifically, the approach clusters mentions of groups of persons that act as non-named entity actors in the texts, e.g., "migrant families"' = "asylum-seekers." Compared to our baseline, the approach keeps the mentions of the geopolitical entities separated, e.g., "Iran leaders" != "European leaders," and clusters (in)directly related mentions with diverse wording, e.g., "American officials" = "Trump Administration."

 

Zhukova, Anastasia (1); Hamborg, Felix (2); Donnay, Karsten (3); Gipp, Bela (1)

1: University of Wuppertal, Germany

2: University of Konstanz, Germany

3: University of Zurich, Switzerland

 

(223) Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings

Keywords: Media bias, news slant, context analysis, word embeddings

Slanted news coverage, also called media bias, can heavily influence how news consumers interpret and react to the news. To automatically identify biased language, we present an exploratory approach that compares the context of related words. We train two word embedding models, one on texts of left-wing, the other on right-wing news outlets. Our hypothesis is that a word's representations in both word embedding spaces are more similar for non-biased words than biased words. The underlying idea is that the context of biased words in different news outlets varies more strongly than the one of non-biased words, since the perception of a word as being biased differs depending on its context. While we do not find statistical significance to accept the hypothesis, the results show the effectiveness of the approach. For example, after a linear mapping of both word embeddings spaces, 31% of the words with the largest distances potentially induce bias. To improve the results, we find that the dataset needs to be significantly larger, and we derive further methodology as future research direction. To our knowledge, this paper presents the first in-depth look at the context of bias words measured by word embeddings.

 

Spinde, Timo (1,2); Rudnitckaia, Lada (2); Hamborg, Felix (2,3); Gipp, Bela (1,3)

1: University of Wuppertal, Germany

2: University of Konstanz, Germany

3: Heidelberg Academy of Sciences and Humanities, Germany

 

(330) Towards Target-dependent Sentiment Classification in News Articles

Keywords: sentiment classification, sentiment analysis, news bias, media bias, news articles

Extensive research on target-dependent sentiment classification (TSC) has led to strong classification performances in domains where authors tend to explicitly express sentiment about specific entities or topics, such as in reviews or on social media. We investigate TSC in news articles, a much less researched domain despite the importance of news as an essential information source in individual and societal decision making. This article introduces NewsTSC, a manually annotated dataset to explore TSC on news articles. Investigating characteristics of sentiment in news and contrasting them to popular TSC domains, we find that sentiment in the news is expressed less explicitly, is more dependent on context and readership, and requires a greater degree of interpretation. In an extensive evaluation, we find that the current state-of-the-art in TSC performs worse on news articles than on other domains (average recall AvgRec=69.8 on NewsTSC compared to AvgRev=[ 75.6, 82.2 ] on established TSC datasets). Reasons include incorrectly resolved relation of target and sentiment-bearing phrases and off-context dependence. As a major improvement over previous news TSC, we find that BERT's natural language understanding capabilities strongly better capture the less explicit sentiment used in news articles.

 

Hamborg, Felix (1); Donnay, Karsten (2); Gipp, Bela (3)

1: University of Konstanz, Germany

2: University of Zurich, Switzerland

3: University of Wuppertal, Germany

23/03/2021 12:00 +00:00 - 23/03/2021 13:00 +00:00
(23/03/2021 12:00 +00:00)
| Short Research Papers | 32 Attendees
Short Research Papers 5 (Short Research Papers)
Simon Mahony
Simon Mahony
Professor, Beijing Normal University at Zhuhai
Yaming Fu
Yaming Fu
PhD candidate, UCL (University College London)
Yohanan Ouaknine
Yohanan Ouaknine
Antonio Lucas Soares
Antonio Lucas Soares
Professor | Head of Research, University of Porto and INESCTEC

(254) Encouraging Diversity of Dialogue as part of the iSchools Agenda

Keywords: Diversity, Community, Globalisation

This paper takes the conference themes of Diversity, Divergence, Dialogue and applies them to an analysis of the published topic headings and keywords from previous iConferences to determine the extent to which diversity is an important aspect within the iSchools community. It follows previous research from 2016 where Bogers and Greifeneder conducted a quantitative analysis of the metrics for submission and acceptance of papers for the 2014 iConference in Berlin. Their interest was in the potential for bias resulting from a lack of diversity in the established review process. We look at topic headings, language and country of presenters as a sub-set of diversity and how we might move away from the Anglophone dominance towards more demographic diversity and in doing so widen the channels for scholarly communication and dialogue. The move to a virtual conference removes any geolocational difficulties and competition for limited travel budgets. The 2021 Chinese track accepts submissions in Chinese, removing the difficulties of the English-language requirement for scholars of the host nation. Language, publication and travel are determining factors for encouraging and facilitating diversity; these should be reinforced within the iSchools movement to develop a sense of community with members as stakeholders so that they feel that they are part of a diverse but inclusive community. This Short Paper is the first stage in a wider study looking at the changes that the innovations for the 2021 iConference have on diversity, divergence, and dialogue for papers and published proceedings.

 

Mahony, Simon (1); Fu, Yaming (2)

1: Research Centre for Digital Publishing and Digital Humanities, Beijing Normal University at Zhuhai, 519087, China

2: Department of Information Studies, University College London (UCL), UK

 

(158) Information practices of French-speaking immigrants to Israel: An exploratory study

Keywords: Information practice, information sources, information needs, immigrants, immigration policy

This preliminary study focuses on information practices of French-speaking immigrants to Israel with three goals in mind: a) understanding their infor-mation needs; b) mapping information sources used before and after immigra-tion to cope with these needs, and c) analyzing the information practices relat-ed to immigrant's wellbeing. The Israeli law allows immigration and citizen-ship for any person of Jewish ascendant, and Israel is the fifth country in OECD by immigrants share in its population. Immigration is not only mobility but also a significant transition in life, impacting on immigrant's wellbeing, levels of income, health, and housing conditions. Efficient information prac-tice plays an essential role in coping with these issues.

Methodology

French questionnaires were published on Facebook and LinkedIn groups dealing with immigration to Israel in August and September 2020. Seventy-one responses were collected.

Findings

This preliminary study revealed a shift in Jewish immigrants' information sources to Israel, from familial and organizational to digital information sources. A second finding is a factor analysis of the main topics researched by immigrants, developed in three components: Integration, Short-term settle-ment, and long-term settlement. The last finding shows how these components are correlated to information sources used after immigration.

Originality

Original aspects of this preliminary study are exploring information sources before and after immigration and their correlation to immigrants' information needs. These findings may also pave the way to include information practices in immigration policy and government agencies' work.

 

Ouaknine, Yohanan Independent Researcher, Israel

23/03/2021 14:00 +00:00 - 23/03/2021 15:30 +00:00
(23/03/2021 14:00 +00:00)
| Short Research Papers | 42 Attendees
Short Research Papers 6 (Short Research Papers)

(138) Producing Web Content Within Platform/Infrastructure Hybrids

Keywords: Content Management, Data Modeling, Infrastructures, Platforms

While web content management systems (CMSs) play important roles in shaping web content, they have received very little attention from scholars working in information studies or related fields concerned with the inter-section of society and technology. This paper first situates CMSs within an emerging discussion of platform/infrastructure hybrids. It then presents a limited case study of how the concept of structured content is implemented within the social and technical constraints of the widely used Wordpress CMS, indicating ways that the study of CMSs can contribute to theory on platform/infrastructure hybrids.

 

Carter, Daniel Texas State University

United States of America

 

(139) Information Systems as Mediators of Freedom of Infor-mation Requests

Keywords: Freedom of information, Open Government Data, Information Systems

While Freedom of Information requests play an important role in government oversight, the process remains largely untheorized, especially in rela-tion to the role of information systems. To address this gap, we conducted an exploratory study using a random, stratified sample of 96 municipalities in one state. Our findings suggest that information systems play multiple mediating roles in shaping and affording access to government records, and that this mediation influences the outcomes of the FOI process. Our work has practical implications for transparency advocates, IS designers, and oth-er information professionals.

 

Carter, Daniel (1); Stratton, Caroline (2)

1: Texas State University, United States of America

2: Florida State University

 

(235) The Model of Influence in Cybersecurity with Frames

Keywords: Cybersecurity, Framing, Frames, Information Security, Schema

The Model of Influence in Cybersecurity with Frames unifies the current literature around influence and media effects in cybersecurity messaging. Building on the Process Model of Framing Research by Scheufele, this new model applies directly to the cybersecurity area and provides a macro-level view to further researcher understand of cybersecurity influence and pro-vide options for intervention by organizational security professionals. This analysis included 42 documents concerning the work of influencing users to engage in secure behavior covering topics in persuasion, user interface design, equivalency framing, managing, and understanding user perceptions, and exploring user mental models regarding cybersecurity. This review also investigates the use of framing in cybersecurity and the definitions needed to contextualize and understand research in cybersecurity that uses framing. This model is intended as a starting point with which to build a larger un-derstanding of cybersecurity communication to address human factors in cybersecurity.

 

Romero-Masters, Philip University of Wisconsin Madison

United States of America

23/03/2021 16:00 +00:00 - 23/03/2021 17:30 +00:00
(23/03/2021 16:00 +00:00)
| Plenary | 78 Attendees
(736) Data Feminism (Plenary)
Catherine D'Ignazio
Catherine D'Ignazio
Assistant Professor of Urban Science and Planning, MIT
LK
Lauren Klein

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists--and others who rely on data in their work--to ignore. But it is precisely this power that makes it worth asking: "Data science by whom? Data science for whom? Data science with whose interests in mind? These are some of the questions that emerge from what we call data feminism, a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought. Illustrating data feminism in action, this talk will show how challenges to the male/female binary can help to challenge other hierarchical (and empirically wrong) classification systems; it will explain how an understanding of emotion can expand our ideas about effective data visualization; how the concept of invisible labor can expose the significant human efforts required by our automated systems; and why the data never, ever “speak for themselves.” The goal of this talk, as with the project of data feminism, is to model how scholarship can be transformed into action: how feminist thinking can be operationalized in order to imagine more ethical and equitable data practices.

 

(1) Catherine D'Ignazio and (2) Lauren F. Klein

1: Catherine D'Ignazio
Assistant Professor of Urban Science & Planning
Director, Data + Feminism Lab
Department of Urban Studies & Planning, MIT

2: Lauren F. Klein, Ph.D.
Associate Professor
Departments of English and Quantitative Theory & Methods
Emory University, US

23/03/2021 19:00 +00:00 - 23/03/2021 20:30 +00:00
(23/03/2021 19:00 +00:00)
| Full Research Papers | 35 Attendees
Full Research Papers 5 (Full Research Papers)
CP
Chelsea K. Palmer
Operations Manager, Countable Web Productions
MZ
Mingrui Zhang
Ph.D. Candidate, University of Washington
Pnina Fichman
Pnina Fichman
Professor of Information Science, Indiana University - Bloomington
RB
Rachel Brill
NV
Nitin Verma
Ph.D. Student, The University of Texas at Austin

(398) Multidisciplinary Blockchain Pedagogy and Design: A Case Study in Moving from Theory to Pedagogy to Practice

Keywords: Multidisciplinarity, Design, Blockchain, Pedagogy

The application of multidisciplinary theoretical models in an emerging field of study like blockchain can improve both collaborative learning and solution design, especially by creating a valuable shared language for colleagues from different disciplinary areas. This tripartite paper traces a journey from theory to practice by outlining the origin and development of the theoretical ‘three layer trust model’ for blockchain technologies, discussing the pedagogical utility of this model within a virtual education setting, and describing a student’s application of the learned model in a technical blockchain product design setting. By providing a thorough grounding in the complex multidisciplinary balance involved in designing blockchain systems (and adding the autoethnographic reflections of participants in this multi-setting focal design application) the following paper supports the potential value of such theoretical models to establish shared language for complex concepts across disciplinary divides. Future research directions are suggested to establish greater validity for the concepts presented within this paper and dive deeper into the foundations of its many referenced disciplines.

 

Palmer, Chelsea Kathleen (1); Rowell, Christopher (2); Lemieux, Victoria L. (1)

1: School of Information, University of British Columbia, Canada

2: Sauder School of Business, University of British Columbia, Canada

 

(166) A Comparative Study of Lexical and Semantic Emoji Suggestion Systems

Keywords: emoji suggestion, empirical study, text messaging, online communication

Emoji suggestion systems based on typed text have been proposed to encourage emoji usage and enrich text messaging; however, such systems’ actual effects on the chat experience are unknown. We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared these in two different studies. To investigate the effect of emoji suggestion in online conversations, we conducted a laboratory text-messaging study with 24 participants, and also a 15-day longitudinal field deployment with 18 participants. We found that participants picked more semantic suggestions than lexical suggestions, and they perceive the semantic suggestions as more relevant to the message content. Our subjective data showed that although the suggestion mechanism did not affect the chatting experience significantly, different mechanisms could change the composing behavior of the users and facilitate their emoji-searching needs in different ways.

 

Zhang, Mingrui (1); Mariakakis, Alex (2); Burke, Jacob (1); Wobbrock, Jacob O. (1)

1: University of Washington, United States of America

2: University of Toronto, Canada

 

(626 The Impact Of Question Type And Topic On Misinformation And Trolling On Yahoo! Answers

Keywords: question answering sites, trolling, misinformation, question type

Trolling and misinformation are ubiquitous on social media platforms, such as Yahoo! Answers. Yet, little is known about the impact of question type and topic on the extent of trolling and misinformation in answers on these platforms. We address this gap by analyzing 120 transactions with 2000 answers from two Yahoo! Answers categories: Politics & Government and Society & Culture. We found that trolling and misinformation are widespread on Yahoo! Answers. In most cases, trolling in questions were echoed with more trolling in answers, and misinformation in questions with more misinformation in answers. We also found that 1) more misinformation and more trolling were found in answers to conversational questions than to informational questions; 2) more misinformation in answers to question in politics than answers to questions in culture; and 3) trolling significantly differed between politics and culture.

 

Fichman, Pnina; Brill, Rachel

Indiana University, United States of America

23/03/2021 21:30 +00:00 - 23/03/2021 23:00 +00:00
(23/03/2021 21:30 +00:00)
| Short Research Papers | 45 Attendees
Short Research Papers 7 (Short Research Papers)
Rongqian Ma
Rongqian Ma
PhD Candidate, University of Pittsburgh
Kahyun Choi
Kahyun Choi
Assistant Professor, Indiana University Bloomington
LD
Lisa Dirks
PhD Candidate, University of Washington
Stefanie Havelka
Stefanie Havelka
recent PhD graduate

(258) Understanding the Narrative Functions of Visualization in Digital Humanities Publications: A Case Study of the Journal of Cultural Analytics

Keywords: Data visualization, digital humanities, visual rhetoric, scholarly communication, Journal of Cultural Analytics

The use and effects of visual representations in knowledge production have been a charged topic in scientific research. In the field of humanities studies, however, this topic remains under-examined despite the increasing applications of data visualization in the field. This paper aims to understand how visual representations facilitate narrative construction in published articles in the emerging field of digital humanities (DH). Through the methods of content analysis and close reading, we analyzed the narrative functions of visualizations in the argumentation process with a selected sample of research articles published in the Journal of Cultural Analytics from 2017 to 2019. With four observations from the analysis, this study presented a preliminary yet innovative examination of DH’s visual language and proposed suggestions on integrating existing functional frameworks of data visualization with the research contexts of digital humanities.

 

Ma, Rongqian (1); Li, Kai (2); He, Daqing (1)

1: University of Pittsburgh, United States of America

2: Renmin University of China, China

 

(265) Bimodal Music Subject Classification via Context-Dependent Language Models

Keywords: Music Subject Classification, Language Model, BERT

This work presents a bimodal music subject classification method that uses two different inputs: lyrics and user interpretations of lyrics. While the subject has been an essential metadata type that the music listeners and providers have wanted to use to categorize their music database, it has been difficult to directly utilize it directly due to the subjective nature of song lyrics analysis. We advance automatic subject classification technology by employing a context-dependent language model, bidirectional encoder representations from the Transformers (BERT). BERT is a promising solution to reduce the gap between humans and machines' abilities to understand lyrics because it transforms a word into a feature vector by harmonizing the contextual relationship between that word and its surrounding words. The proposed model employs two BERT modules as an ensemble to control the contribution of the two modalities. It shows significant improvement over the existing context-independent models on both the uni and bimodal subject classification benchmarks, suggesting that BERT's context-dependent features can help the machine learning models uncover the poetic nature of song lyrics.

 

Choi, Kahyun

Indiana University Bloomington United States of America

 

(491) Collaborative Research Results Dissemination: Applying Postcolonial Theory to Indigenous Community Collaboration in Health Research Results Dissemination

Keywords: Indigenous research, results dissemination, postcolonial theory, decolonization, collaboration

Community engagement in research has become increasingly prominent; it is essential for research conducted with Indigenous communities. In some cases, community members are receptively engaged in research from beginning to end, but this is inconsistent. Community collaboration during the results dissemination process is an element of engagement that is consistently overlooked or otherwise ineffectively executed. The concept of decolonizing research and the postcolonial theoretical foundations of decolonization are explored in this paper. Decolonizing research involves conducting research with Indigenous communities that places Indigenous voices and epistemologies at the center of the research process. This paper considers a decolonization framework to examine Indigenous community collaboration in the research results dissemination process including recommendations for applying postcolonial theory in the design of technologies to facilitate collaborative research results dissemination.

 

Dirks, Lisa Grace

University of Washington, United States of America

23/03/2021 16:00 +00:00 - 23/03/2021 17:30 +00:00
(23/03/2021 16:00 +00:00)
| Plenary | 78 Attendees
(736) Data Feminism
Catherine D'Ignazio
Catherine D'Ignazio
Assistant Professor of Urban Science and Planning, MIT
LK
Lauren Klein

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists--and others who rely on data in their work--to ignore. But it is precisely this power that makes it worth asking: "Data science by whom? Data science for whom? Data science with whose interests in mind? These are some of the questions that emerge from what we call data feminism, a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought. Illustrating data feminism in action, this talk will show how challenges to the male/female binary can help to challenge other hierarchical (and empirically wrong) classification systems; it will explain how an understanding of emotion can expand our ideas about effective data visualization; how the concept of invisible labor can expose the significant human efforts required by our automated systems; and why the data never, ever “speak for themselves.” The goal of this talk, as with the project of data feminism, is to model how scholarship can be transformed into action: how feminist thinking can be operationalized in order to imagine more ethical and equitable data practices.

 

(1) Catherine D'Ignazio and (2) Lauren F. Klein

1: Catherine D'Ignazio
Assistant Professor of Urban Science & Planning
Director, Data + Feminism Lab
Department of Urban Studies & Planning, MIT

2: Lauren F. Klein, Ph.D.
Associate Professor
Departments of English and Quantitative Theory & Methods
Emory University, US

23/03/2021 19:00 +00:00 - 23/03/2021 20:30 +00:00
(23/03/2021 19:00 +00:00)
| Full Research Papers | 35 Attendees
Full Research Papers 5
CP
Chelsea K. Palmer
Operations Manager, Countable Web Productions
MZ
Mingrui Zhang
Ph.D. Candidate, University of Washington
Pnina Fichman
Pnina Fichman
Professor of Information Science, Indiana University - Bloomington
RB
Rachel Brill
NV
Nitin Verma
Ph.D. Student, The University of Texas at Austin

(398) Multidisciplinary Blockchain Pedagogy and Design: A Case Study in Moving from Theory to Pedagogy to Practice

Keywords: Multidisciplinarity, Design, Blockchain, Pedagogy

The application of multidisciplinary theoretical models in an emerging field of study like blockchain can improve both collaborative learning and solution design, especially by creating a valuable shared language for colleagues from different disciplinary areas. This tripartite paper traces a journey from theory to practice by outlining the origin and development of the theoretical ‘three layer trust model’ for blockchain technologies, discussing the pedagogical utility of this model within a virtual education setting, and describing a student’s application of the learned model in a technical blockchain product design setting. By providing a thorough grounding in the complex multidisciplinary balance involved in designing blockchain systems (and adding the autoethnographic reflections of participants in this multi-setting focal design application) the following paper supports the potential value of such theoretical models to establish shared language for complex concepts across disciplinary divides. Future research directions are suggested to establish greater validity for the concepts presented within this paper and dive deeper into the foundations of its many referenced disciplines.

 

Palmer, Chelsea Kathleen (1); Rowell, Christopher (2); Lemieux, Victoria L. (1)

1: School of Information, University of British Columbia, Canada

2: Sauder School of Business, University of British Columbia, Canada

 

(166) A Comparative Study of Lexical and Semantic Emoji Suggestion Systems

Keywords: emoji suggestion, empirical study, text messaging, online communication

Emoji suggestion systems based on typed text have been proposed to encourage emoji usage and enrich text messaging; however, such systems’ actual effects on the chat experience are unknown. We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared these in two different studies. To investigate the effect of emoji suggestion in online conversations, we conducted a laboratory text-messaging study with 24 participants, and also a 15-day longitudinal field deployment with 18 participants. We found that participants picked more semantic suggestions than lexical suggestions, and they perceive the semantic suggestions as more relevant to the message content. Our subjective data showed that although the suggestion mechanism did not affect the chatting experience significantly, different mechanisms could change the composing behavior of the users and facilitate their emoji-searching needs in different ways.

 

Zhang, Mingrui (1); Mariakakis, Alex (2); Burke, Jacob (1); Wobbrock, Jacob O. (1)

1: University of Washington, United States of America

2: University of Toronto, Canada

 

(626 The Impact Of Question Type And Topic On Misinformation And Trolling On Yahoo! Answers

Keywords: question answering sites, trolling, misinformation, question type

Trolling and misinformation are ubiquitous on social media platforms, such as Yahoo! Answers. Yet, little is known about the impact of question type and topic on the extent of trolling and misinformation in answers on these platforms. We address this gap by analyzing 120 transactions with 2000 answers from two Yahoo! Answers categories: Politics & Government and Society & Culture. We found that trolling and misinformation are widespread on Yahoo! Answers. In most cases, trolling in questions were echoed with more trolling in answers, and misinformation in questions with more misinformation in answers. We also found that 1) more misinformation and more trolling were found in answers to conversational questions than to informational questions; 2) more misinformation in answers to question in politics than answers to questions in culture; and 3) trolling significantly differed between politics and culture.

 

Fichman, Pnina; Brill, Rachel

Indiana University, United States of America

All Events
# Gamification
# News
23/03/2021 00:00 +00:00 - 23/03/2021 01:30 +00:00
(23/03/2021 00:00 +00:00)
| Short Research Papers | 33 Attendees
Short Research Papers 2

(320) Becoming open knowledge institutions: divergence, dialogue and diversity

Keywords: Open Knowledge Institutions, Open Access performance, Higher education, Data visualization

The Curtin Open Knowledge Initiative (COKI) is an innovative research project that collects and analyses publicly available research output data to assist and encourage re-searchers, academics, administrators and executives to understand the actual and potential reach of openness in research, and to assess their progress on the path towards open knowledge institutions. By taking a broad global approach and using multiple data sources, the project diverges from existing approaches, methods and bibliometric measures in the scholarly research environment. It combines analysis of research output, citations, publication sources and publishers, funders, and social media events, open and not open access to provide overviews of research output and performance at institutional, funder, consortial and country levels. The project collects and analyses personnel diversity data such as gender and origin, focusing on widening the reach of data analysis to emphasise the importance and value of diversity in research and knowledge production. Interactive visual tools present research output and performance to encourage understanding and dialogue among researchers and managers. The path towards becoming open knowledge institutions involves a process of cultural change, moving beyond dominant publishing practices. This paper discusses how through divergence, diversity and dialogue the COKI project can contribute to this change, with examples of data use in understanding and embracing openness.

 

Wilson, Katie (1); Montgomery, Lucy (1); Neylon, Cameron (1); Handcock, Rebecca N. (2); Hosking, Richard (2); Huang, Chun-Kai {Karl} (1); Ozaygen, Alkim (1); Roelofs, Aniek (2)

1: Centre for Culture and Technology, Curtin University, Australia

2: Curtin Institute for Computation, Curtin University, Australia

 

(199) Aggregation and Utilization of Metadata for Intangible Folk Cultural Properties Using Linked Open Data

Keywords: Intangible Folk Cultural Properties, Metadata, Linked Open Data, CIDOC CRM, SPARQL

Intangible Folk Cultural Properties (IFCP) represent cultural customs or events related to transition in people's lives, and need to be protected and passed on to future generations. The Japanese government adopted the revised Act on Protection of Cultural Properties in 2018, which aims to ensure comprehensive protection and utilization of cultural properties. IFCP are required to make it available and accessible to the public considering these features. This study proposes an IFCP data model using Linked Open Data (LOD). This model is based on the CIDOC Conceptual Reference Model (CRM) and other vocabularies. We constructed a dataset based on this model and published it on the web. The dataset contains 5,106 triples from 103 IFCP focusing on religious faiths festivals (RF) and annual observances (AO). To evaluate our data model, we defined functional requirements for the IFCP and implemented a prototype system to verify utilization feasibility of the IFCP. The prototype system shows the IFCP lists based on retrieval feature using the SPARQL query language.

 

Sato, Itsumi; Takaku, Masao

University of Tsukuba, Japan

 

(342) Research on the Decision-making Process of Public Personnel Resisting Open Data Motivated by Perceived Risks

Based on the cognition of stakeholders, this paper reveals the decision-making process of civil servants resisting open data based on perceived risks. Adopting grounded theory, this study interviewed 22 stakeholders to collect data and then identified four factors as the pillars of the theoretical framework: perception of risks, conservative organizational culture, insufficient external pressure and poor operability. After that, this paper constructed a model for the decision path, which explains the formation of perceived risks of civil servants, and it al-so explains how the perceived risks are transformed into resistance motivation and make a behavior decision. Based on the level of certainty, the decision envi-ronment can be divided into the resistance decision path under the determined environment and that under the uncertain environment. This study also summa-rizes that accountability and loss of interest are two types of risk that can be considered when civil servants decide not to open data.

 

Li, Si (1); Chen, Yi (2)

1: Peking University

2: Wuhan University

23/03/2021 05:00 +00:00 - 23/03/2021 06:00 +00:00
(23/03/2021 05:00 +00:00)
| Short Research Papers | 28 Attendees
Short Research Papers 3

(264) A Meta-Review of Gamification Research

Keywords: Gamification, Gamification Review, Meta-Review

Gamification has gained significant attention from academia and industry in the recent decade. Correspondingly, there has been a prolific publication rec-ord on gamification research. This research aims to explore a landscape view of gamification research through a meta-review, a systematical assessment of a collection of gamification literature reviews. The meta-review addresses four research questions on (1) literature review scope, (2) application do-mains, (3) review types, and (4) review foci in 48 reviews published from January 2018 to June 2020. This research contributes to a high-level over-view of the state of development in the gamification field. It also demon-strates a process of conducting meta-reviews.

 

Zhang, Ping (1); Tang, Jian (2); Jeong, Eunmi{Ellie} (1)

1: Syracuse University, USA

2: Central University of Finance and Economics, China

 

(293) A pilot ethnographic study of gamified English learning among Primary Four and Five students in a rural Chinese primary school

Keywords: Gamification, English reading literacy, self-determination theory, rural school

This pilot ethnographic study examines the feasibility of learning English with a gamified English e-learning platform among Primary Four (P4) and Primary Five (P5) students in a remote primary school in Henan, China. Forty-one students participated in a summer reading camp where the gamified platform in question was used. Results show that following 4 weeks of playing on the gamified platform, the majority of students developed substantial interest in reading more English books upon the fulfillment of their innate psychological needs for competence, relatedness and autonomy. The authors conclude that under a self-determination framework, the gamified platform has been effective in helping Chinese students in a rural community to learn English.

 

Meng, Na (1); Lee, Cameron S.Y. (2); Chu, Samuel K.W. (2)

1: Jinling Institute of Technology, Nanjing, China

2: Faculty of Education, the University of Hong Kong, Hong Kong, China

23/03/2021 09:30 +00:00 - 23/03/2021 11:00 +00:00
(23/03/2021 09:30 +00:00)
| Short Research Papers | 24 Attendees
Short Research Papers 4
Anastasia Zhukova
Anastasia Zhukova
Doctoral Researcher, University of Wuppertal
Timo Michael Spinde
Timo Michael Spinde
Ph.D., University of Wuppertal
Felix Hamborg
Felix Hamborg
Doctoral Researcher, University of Konstanz
TB
Toine Bogers
Asssociate professor, Aalborg University Copenhagen

(208) Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons

Keywords: concept identification, news analysis, clustering, media bias

Unsupervised concept identification through clustering, i.e., identification of semantically related words and phrases, is a common approach to identify contextual primitives employed in various use cases, e.g., text dimension reduction, i.e., replace words with the concepts to reduce the vocabulary size, summarization, and named entity resolution. We demonstrate the first results of an unsupervised approach for the identification of groups of persons as actors extracted from a set of related articles. Specifically, the approach clusters mentions of groups of persons that act as non-named entity actors in the texts, e.g., "migrant families"' = "asylum-seekers." Compared to our baseline, the approach keeps the mentions of the geopolitical entities separated, e.g., "Iran leaders" != "European leaders," and clusters (in)directly related mentions with diverse wording, e.g., "American officials" = "Trump Administration."

 

Zhukova, Anastasia (1); Hamborg, Felix (2); Donnay, Karsten (3); Gipp, Bela (1)

1: University of Wuppertal, Germany

2: University of Konstanz, Germany

3: University of Zurich, Switzerland

 

(223) Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings

Keywords: Media bias, news slant, context analysis, word embeddings

Slanted news coverage, also called media bias, can heavily influence how news consumers interpret and react to the news. To automatically identify biased language, we present an exploratory approach that compares the context of related words. We train two word embedding models, one on texts of left-wing, the other on right-wing news outlets. Our hypothesis is that a word's representations in both word embedding spaces are more similar for non-biased words than biased words. The underlying idea is that the context of biased words in different news outlets varies more strongly than the one of non-biased words, since the perception of a word as being biased differs depending on its context. While we do not find statistical significance to accept the hypothesis, the results show the effectiveness of the approach. For example, after a linear mapping of both word embeddings spaces, 31% of the words with the largest distances potentially induce bias. To improve the results, we find that the dataset needs to be significantly larger, and we derive further methodology as future research direction. To our knowledge, this paper presents the first in-depth look at the context of bias words measured by word embeddings.

 

Spinde, Timo (1,2); Rudnitckaia, Lada (2); Hamborg, Felix (2,3); Gipp, Bela (1,3)

1: University of Wuppertal, Germany

2: University of Konstanz, Germany

3: Heidelberg Academy of Sciences and Humanities, Germany

 

(330) Towards Target-dependent Sentiment Classification in News Articles

Keywords: sentiment classification, sentiment analysis, news bias, media bias, news articles

Extensive research on target-dependent sentiment classification (TSC) has led to strong classification performances in domains where authors tend to explicitly express sentiment about specific entities or topics, such as in reviews or on social media. We investigate TSC in news articles, a much less researched domain despite the importance of news as an essential information source in individual and societal decision making. This article introduces NewsTSC, a manually annotated dataset to explore TSC on news articles. Investigating characteristics of sentiment in news and contrasting them to popular TSC domains, we find that sentiment in the news is expressed less explicitly, is more dependent on context and readership, and requires a greater degree of interpretation. In an extensive evaluation, we find that the current state-of-the-art in TSC performs worse on news articles than on other domains (average recall AvgRec=69.8 on NewsTSC compared to AvgRev=[ 75.6, 82.2 ] on established TSC datasets). Reasons include incorrectly resolved relation of target and sentiment-bearing phrases and off-context dependence. As a major improvement over previous news TSC, we find that BERT's natural language understanding capabilities strongly better capture the less explicit sentiment used in news articles.

 

Hamborg, Felix (1); Donnay, Karsten (2); Gipp, Bela (3)

1: University of Konstanz, Germany

2: University of Zurich, Switzerland

3: University of Wuppertal, Germany

23/03/2021 12:00 +00:00 - 23/03/2021 13:00 +00:00
(23/03/2021 12:00 +00:00)
| Short Research Papers | 32 Attendees
Short Research Papers 5
Simon Mahony
Simon Mahony
Professor, Beijing Normal University at Zhuhai
Yaming Fu
Yaming Fu
PhD candidate, UCL (University College London)
Yohanan Ouaknine
Yohanan Ouaknine
Antonio Lucas Soares
Antonio Lucas Soares
Professor | Head of Research, University of Porto and INESCTEC

(254) Encouraging Diversity of Dialogue as part of the iSchools Agenda

Keywords: Diversity, Community, Globalisation

This paper takes the conference themes of Diversity, Divergence, Dialogue and applies them to an analysis of the published topic headings and keywords from previous iConferences to determine the extent to which diversity is an important aspect within the iSchools community. It follows previous research from 2016 where Bogers and Greifeneder conducted a quantitative analysis of the metrics for submission and acceptance of papers for the 2014 iConference in Berlin. Their interest was in the potential for bias resulting from a lack of diversity in the established review process. We look at topic headings, language and country of presenters as a sub-set of diversity and how we might move away from the Anglophone dominance towards more demographic diversity and in doing so widen the channels for scholarly communication and dialogue. The move to a virtual conference removes any geolocational difficulties and competition for limited travel budgets. The 2021 Chinese track accepts submissions in Chinese, removing the difficulties of the English-language requirement for scholars of the host nation. Language, publication and travel are determining factors for encouraging and facilitating diversity; these should be reinforced within the iSchools movement to develop a sense of community with members as stakeholders so that they feel that they are part of a diverse but inclusive community. This Short Paper is the first stage in a wider study looking at the changes that the innovations for the 2021 iConference have on diversity, divergence, and dialogue for papers and published proceedings.

 

Mahony, Simon (1); Fu, Yaming (2)

1: Research Centre for Digital Publishing and Digital Humanities, Beijing Normal University at Zhuhai, 519087, China

2: Department of Information Studies, University College London (UCL), UK

 

(158) Information practices of French-speaking immigrants to Israel: An exploratory study

Keywords: Information practice, information sources, information needs, immigrants, immigration policy

This preliminary study focuses on information practices of French-speaking immigrants to Israel with three goals in mind: a) understanding their infor-mation needs; b) mapping information sources used before and after immigra-tion to cope with these needs, and c) analyzing the information practices relat-ed to immigrant's wellbeing. The Israeli law allows immigration and citizen-ship for any person of Jewish ascendant, and Israel is the fifth country in OECD by immigrants share in its population. Immigration is not only mobility but also a significant transition in life, impacting on immigrant's wellbeing, levels of income, health, and housing conditions. Efficient information prac-tice plays an essential role in coping with these issues.

Methodology

French questionnaires were published on Facebook and LinkedIn groups dealing with immigration to Israel in August and September 2020. Seventy-one responses were collected.

Findings

This preliminary study revealed a shift in Jewish immigrants' information sources to Israel, from familial and organizational to digital information sources. A second finding is a factor analysis of the main topics researched by immigrants, developed in three components: Integration, Short-term settle-ment, and long-term settlement. The last finding shows how these components are correlated to information sources used after immigration.

Originality

Original aspects of this preliminary study are exploring information sources before and after immigration and their correlation to immigrants' information needs. These findings may also pave the way to include information practices in immigration policy and government agencies' work.

 

Ouaknine, Yohanan Independent Researcher, Israel

23/03/2021 14:00 +00:00 - 23/03/2021 15:30 +00:00
(23/03/2021 14:00 +00:00)
| Short Research Papers | 42 Attendees
Short Research Papers 6

(138) Producing Web Content Within Platform/Infrastructure Hybrids

Keywords: Content Management, Data Modeling, Infrastructures, Platforms

While web content management systems (CMSs) play important roles in shaping web content, they have received very little attention from scholars working in information studies or related fields concerned with the inter-section of society and technology. This paper first situates CMSs within an emerging discussion of platform/infrastructure hybrids. It then presents a limited case study of how the concept of structured content is implemented within the social and technical constraints of the widely used Wordpress CMS, indicating ways that the study of CMSs can contribute to theory on platform/infrastructure hybrids.

 

Carter, Daniel Texas State University

United States of America

 

(139) Information Systems as Mediators of Freedom of Infor-mation Requests

Keywords: Freedom of information, Open Government Data, Information Systems

While Freedom of Information requests play an important role in government oversight, the process remains largely untheorized, especially in rela-tion to the role of information systems. To address this gap, we conducted an exploratory study using a random, stratified sample of 96 municipalities in one state. Our findings suggest that information systems play multiple mediating roles in shaping and affording access to government records, and that this mediation influences the outcomes of the FOI process. Our work has practical implications for transparency advocates, IS designers, and oth-er information professionals.

 

Carter, Daniel (1); Stratton, Caroline (2)

1: Texas State University, United States of America

2: Florida State University

 

(235) The Model of Influence in Cybersecurity with Frames

Keywords: Cybersecurity, Framing, Frames, Information Security, Schema

The Model of Influence in Cybersecurity with Frames unifies the current literature around influence and media effects in cybersecurity messaging. Building on the Process Model of Framing Research by Scheufele, this new model applies directly to the cybersecurity area and provides a macro-level view to further researcher understand of cybersecurity influence and pro-vide options for intervention by organizational security professionals. This analysis included 42 documents concerning the work of influencing users to engage in secure behavior covering topics in persuasion, user interface design, equivalency framing, managing, and understanding user perceptions, and exploring user mental models regarding cybersecurity. This review also investigates the use of framing in cybersecurity and the definitions needed to contextualize and understand research in cybersecurity that uses framing. This model is intended as a starting point with which to build a larger un-derstanding of cybersecurity communication to address human factors in cybersecurity.

 

Romero-Masters, Philip University of Wisconsin Madison

United States of America

23/03/2021 21:30 +00:00 - 23/03/2021 23:00 +00:00
(23/03/2021 21:30 +00:00)
| Short Research Papers | 45 Attendees
Short Research Papers 7
Rongqian Ma
Rongqian Ma
PhD Candidate, University of Pittsburgh
Kahyun Choi
Kahyun Choi
Assistant Professor, Indiana University Bloomington
LD
Lisa Dirks
PhD Candidate, University of Washington
Stefanie Havelka
Stefanie Havelka
recent PhD graduate

(258) Understanding the Narrative Functions of Visualization in Digital Humanities Publications: A Case Study of the Journal of Cultural Analytics

Keywords: Data visualization, digital humanities, visual rhetoric, scholarly communication, Journal of Cultural Analytics

The use and effects of visual representations in knowledge production have been a charged topic in scientific research. In the field of humanities studies, however, this topic remains under-examined despite the increasing applications of data visualization in the field. This paper aims to understand how visual representations facilitate narrative construction in published articles in the emerging field of digital humanities (DH). Through the methods of content analysis and close reading, we analyzed the narrative functions of visualizations in the argumentation process with a selected sample of research articles published in the Journal of Cultural Analytics from 2017 to 2019. With four observations from the analysis, this study presented a preliminary yet innovative examination of DH’s visual language and proposed suggestions on integrating existing functional frameworks of data visualization with the research contexts of digital humanities.

 

Ma, Rongqian (1); Li, Kai (2); He, Daqing (1)

1: University of Pittsburgh, United States of America

2: Renmin University of China, China

 

(265) Bimodal Music Subject Classification via Context-Dependent Language Models

Keywords: Music Subject Classification, Language Model, BERT

This work presents a bimodal music subject classification method that uses two different inputs: lyrics and user interpretations of lyrics. While the subject has been an essential metadata type that the music listeners and providers have wanted to use to categorize their music database, it has been difficult to directly utilize it directly due to the subjective nature of song lyrics analysis. We advance automatic subject classification technology by employing a context-dependent language model, bidirectional encoder representations from the Transformers (BERT). BERT is a promising solution to reduce the gap between humans and machines' abilities to understand lyrics because it transforms a word into a feature vector by harmonizing the contextual relationship between that word and its surrounding words. The proposed model employs two BERT modules as an ensemble to control the contribution of the two modalities. It shows significant improvement over the existing context-independent models on both the uni and bimodal subject classification benchmarks, suggesting that BERT's context-dependent features can help the machine learning models uncover the poetic nature of song lyrics.

 

Choi, Kahyun

Indiana University Bloomington United States of America

 

(491) Collaborative Research Results Dissemination: Applying Postcolonial Theory to Indigenous Community Collaboration in Health Research Results Dissemination

Keywords: Indigenous research, results dissemination, postcolonial theory, decolonization, collaboration

Community engagement in research has become increasingly prominent; it is essential for research conducted with Indigenous communities. In some cases, community members are receptively engaged in research from beginning to end, but this is inconsistent. Community collaboration during the results dissemination process is an element of engagement that is consistently overlooked or otherwise ineffectively executed. The concept of decolonizing research and the postcolonial theoretical foundations of decolonization are explored in this paper. Decolonizing research involves conducting research with Indigenous communities that places Indigenous voices and epistemologies at the center of the research process. This paper considers a decolonization framework to examine Indigenous community collaboration in the research results dissemination process including recommendations for applying postcolonial theory in the design of technologies to facilitate collaborative research results dissemination.

 

Dirks, Lisa Grace

University of Washington, United States of America

23/03/2021 02:30 +00:00 - 23/03/2021 04:00 +00:00
(23/03/2021 02:30 +00:00)
| Special Presentations | 65 Attendees
(737) Curriculum Committee Reports: Data Science & Digital Humanities
Sam Oh.
Sam Oh.
Professor, Sungkyunkwan University
John Anthony Walsh
John Anthony Walsh
Associate Professor, Indiana University
IS
IL-YEOL SONG
Professor, Drexel University
JM
Javed Mostafa
Professor & Director, The University of North Carolina at Chapel Hill
DW
Dan Wu
Wuhan, China, School of Information Management Wuhan University
LH
Loni Hagen
Assistant Professor, University of South Florida
Simon Mahony
Simon Mahony
Professor, Beijing Normal University at Zhuhai
MARCIA ZENG
MARCIA ZENG
Professor, Kent State University

The iSchools established two curriculum committees to find a unique iSchool approach to data science and to examine what contributions iSchools can make in the emerging discipline of digital humanities. The two committees were composed of experts from the entire iSchools network and investigated diverse aspects of the charge at hand for 2 years. This session will report the results of intense research and suggest a way forward for iSchools.

Full Research Papers
Full Research Papers 6
Full Research Papers 7
Full Research Papers 8
Full Research Papers 9
Short Research Papers
Short Research Papers 8
Short Research Papers 9
Short Research Papers 10
Doctoral Colloquium
Doctoral Colloquium Part 1
Poster
Poster 2
Overall
Full Research Papers
Short Research Papers
Doctoral Colloquium
Poster
24/03/2021 01:00 +00:00 - 24/03/2021 02:30 +00:00
(24/03/2021 01:00 +00:00)
| Short Research Papers | 36 Attendees
Short Research Papers 8 (Short Research Papers)

(132) A Semantic Organization Based on Linked Data and Knowledge Graph Display

Keywords: Ontology, Linked Data, Knowledge Graph, Retrieval System

In the era of big data, data redundancy has become an obstacle to deep reading. The objective of linked data as a new data organization model, is to transform data into structured data following unified standards. The lack of Chinese conceptual terms has seriously hindered the semantization and standardization of Chinese domain ontology. Taking Chinese historical events as an example, ontology technology is used in this paper to standardize the definition of concepts and semantic relations in domain knowledge. Moreover, concepts from text resources are extracted through a deep learning algorithm Bi-LSTM-CRFs and combined with an external knowledge base to realize the fusion of related data within various data sets. Ultimately, the knowledge ontology of historical events is displayed in the way of knowledge graph to further explore the practical application. The results show that the accuracy of the terms extraction of historical events is about 80% indicating the good recognition performance and portability of the model.

 

Wang, Hao (1,2); Li, Yueyan (1,2); Deng, Sanhong (1,2)

1: School of Information Management, Nanjing University, Nanjing

2: Jiangsu Key Laboratory of Data Engineering & Knowledge Service, Nanjing

 

(295) A Comparative Studies of Automatic Query Formulation in Full-text Database Search of Chinese Digital Humanities

Keywords: Automatic Query Formulation, Full-text Database Search, Digital humanities

Query gap is a very serious problem for the full-text database search in the domain of Chinese digital humanities (CDH). These CDH search systems are mainly focused on the improvement of data quality, which ignore the connection between users’ search intents and the system response. We design a two-phase procedure for comparative analysis of the effectiveness of different automatic query formulation in pre-defined tasks, including a prototype system test and a questionnaire-based user study. The experiment shows that compared to query suggestion and query reformulation, query expansion is the most effective automatic query formulation technology with a strong robust performance for user satisfaction, which means it is not sensitive to task categories based on the search intent. The effectiveness of query reformulation and the hybrid methods are limited while query suggestion performs worse in the task for diverse search intent. These findings are believed to be helpful to the reduction of query gap in the full-text database search of Chinese digital humanities, which will foster the development of this field.

 

Yan, Chengxi (1,2); Ho, Tzu-Yi (1,2); Wang, Jun (1,2)

1: Department of Information Management, Peking University, People's Republic of China

2: Digital Humanities Center, Peking University, People's Republic of China

 

(331) An Author Interest Discovery Model armed with Authorship Credit Allocation Scheme

Keywords: Author Interest Discovery, Topic Model, Perplexity

The author interest discovery can help personalized academic recommendation systems. However, many topic models for discovering author interest implicitly assume equal contribution from each coauthor to a target document. To loosen this limitation, a novel model, ATcredit, is proposed to strengthen the Author-Topic (AT) model with an authorship credit allocation scheme, and the collapsed Gibbs sampling is utilized to approximate the posterior and estimate the model parameters. In total, our model considers six counting schemes, including fixed and flexible versions, as well as equal contributors and hyper-authorship strategies.

 

Xu, Shuo (1); Li, Ling (1); Hao, Liyuan (1); An, Xin (2); Yang, Guancan (3)

1: College of Economics and Management,Beijing University of Technology, China, People's Republic of

2: School of Economics and Management,Beijing Forestry University, China, People's Republic of

3: School of Information Resource Management,Renmin University of China, China, People's Republic of

24/03/2021 03:30 +00:00 - 24/03/2021 05:00 +00:00
(24/03/2021 03:30 +00:00)
| Full Research Papers | 21 Attendees
Full Research Papers 6 (Full Research Papers)

(410) Pre-service Librarians’ Perspective on the Role of Participatory Design in Libraries with Youth

Keywords: Informal Learning, Participatory Design, Youth Program, Librarianship, Youth Service

Participatory Design (PD) is a design methodology that incorporates the end us-ers in the design process. An active area of research in PD focuses on designing new technology with children. As more libraries are offering different technolo-gies to their patrons—especially to children—there is an increasing need to think about how to best incorporate such technologies into library services. Recent in-terest in the field has encouraged librarians to situate themselves as designers, and to find creative solutions to the problems that arise in library settings. However, design methods are not widely utilized in the field of library and information sci-ence. In this study, we have interviewed pre-service librarians and children partic-ipants who did participatory design in libraries within a service-learning course. These participatory design sessions focused on incorporating new technologies into library programming. Our study indicates that PD is a possible method for capturing the ethos of librarianship. Pre-service librarians found that PD allowed them to effectively enact values of service, such as democratic participation and creativity, while children valued being heard from adults in the library and help-ing their community.

 

Lee, Kung Jin; Lee, Jin Ha; Yip, Jason C.

University of Washington

 

(240) The Politics of Digitizing Art and Culture in Vietnam: A Case Study on Matca Space of Photography in Hanoi

Keywords: Digitization, Art and Cultural Sector, Vietnam

The nature of work in the art and cultural sector in Hanoi, Vietnam, is changing. The new generation of cultural professionals is harnessing digital technology to display art and cultural collections in innovative and creative ways. Digitization today is not only about creating ‘hidden’ digital archives but, instead, about curating digital art and culture experiences that are publicly accessible. This allows a way to preserve culture, which can be digitally displayed in a contemporary format. The paper presents findings from a case study on Matca Space for Photography (Matca), including semi-structured interviews, secondary data analysis, and a digital ethnography of Matca’s digital platforms. The current study highlights the challenges and opportunities associated with digitization in Vietnam. While there are challenges with digitization due to a lack of technical resources and human resources, using digital platforms can allow cultural professionals an agency to present Vietnamese art and culture to local and international audiences. This has the potential to redress the imbal-ance in representation and redefine digital orientalism.

 

Duester, Emma

Royal Melbourne Institute of Technology (RMIT), Vietnam

 

(175) Counteracting Misinformation in Quotidian Settings

Keywords: Misinformation, fake news, disinformation, information sharing, polarization, Vietnam

Recent studies investigating misinformation spread have been situated within political contexts and have used psychological and technological approaches. In response, this study illuminates everyday life situations where people discover misinformation. Based on interviews conducted in Vietnam, it found that people’s decision to counteract misinformation in part links to their existent relationship with its sharer. People tend to counteract misinformation shared by significant others rather than by strangers. The need to adhere to norms in order to keep the relationships harmonious and to avoid embarrassing the sharer shapes what methods are used to counteract misinformation. The findings demonstrate the role of maintaining relationships in choosing appropriate ways of counteracting misinformation, offering insights for reconciling ideological polarizations in everyday life.

 

Rohman, Abdul

RMIT U Vietnam, Vietnam

24/03/2021 06:00 +00:00 - 24/03/2021 07:30 +00:00
(24/03/2021 06:00 +00:00)
| Poster | 23 Attendees
Poster 2 (Poster)

Please go to the Presentation Library to view posters and talk to the presenters.

24/03/2021 08:00 +00:00 - 24/03/2021 09:30 +00:00
(24/03/2021 08:00 +00:00)
| Full Research Papers | 23 Attendees
Full Research Papers 7 (Full Research Papers)
Florian Meier
Florian Meier
Assistant Professor, Aalborg University Copenhagen
CK
Cindy Kröber
researcher, TU Dresden
CF
Carolyn Fearn
Head of Operations (Teaching and Learning), Sheffield Hallam University
VO
Virginia Ortiz-Repiso
Proffesor, University Carlos III of Madrid

(397) They Each Have Their Forte: An Exploratory Diary Study of Temporary Switching Behavior Between Mobile Messenger Services

Keywords: Mobile computing, Mobile messenger services, Smartphone, Diary study, Temporary switching behavior

Today's smartphone users often use several mobile messaging services alongside each other, even though they typically offer the same features and functionality. Where previous studies have focused on how and why users permanently abandon mobile messaging services and switch to new ones, this study examines the degree to which smartphone users keep switching back and forth between multiple services, and the factors that influence this temporary switching behavior. We used an exploratory research approach in a longitudinal diary study combined with semi-structured interviews. We found that temporary switching behavior is influenced by technological affordances, contextual factors, individual preferences, and the type of conversation. Both positive and negative impacts were identified within these aspects, with some having an indirect influence, revealing the complexity of temporary switching behavior.

 

Meier, Florian; Langberg Schmidt, Amalie; Bogers, Toine

Aalborg University Copenhagen, Denmark

 

(436) German Art History Students’ use of Digital Repositories: an Insight

Keywords: Digital libraries, Art history, Human information behavior, Qualitative re-search, User study

The paper describes a study on art history students’ research behavior and needs connected to digital resources and repositories. It tries to identify aspects of and approaches to improving and developing these repositories. These students make up a large proportion of the users of digital libraries and their content; their supposedly distinct attitude and skill level concerning technology renders them an important group to observe. Qualitative data derives from three focus groups with 25 students from two German universities. Thematic analysis is based on questions concerning research approaches, curriculum, and the students’ connected desires as avid users of technology in everyday life.

 

Kröber, Cindy

TU Dresden, Germany

 

(466) Post-GDPR usage of students' 'Big-data' at UK Universities

Keywords: GDPR, big-data, learning analytics, higher education

Higher education institutions are extensively using students’ ‘big-data’ to develop student services, create management or staff-led interventions and inform their strategic decisions etc. Following the implementation of the European Union's General Data Protection Regulation (GDPR) in 2018, there has been extensive uncertainty regarding the use of students' data. By conducting interviews with various University staff in the UK, this research aims to explore their understanding and usage of students' data, post-GDPR implementation. The findings indicate students' data is primarily used to build learning analytic tools and student-retention activities. Additionally, it was found that the understanding and usage of both big-data and GDPR differed across various Universities' stakeholders, and there is inadequate support available to these stakeholders. Overall, this research indicates the adoption of big-data based learning analytics requires comprehensive development and implementation policies to address the challenges of learning analytics. Therefore, this research proposes such an approach through co-creation with staff and students; institutional research and staff training.

 

Fearn, Carolyn; Koya, Kushwanth

iSchool, College of Business, Technology & Engineering, Sheffield Hallam University, United Kingdom

24/03/2021 15:30 +00:00 - 24/03/2021 17:00 +00:00
(24/03/2021 15:30 +00:00)
| Short Research Papers | 42 Attendees
Short Research Papers 9 (Short Research Papers)
Deborah A Garwood
Deborah A Garwood
PhD candidate, Drexel University
Daniela M. Markazi
Daniela M. Markazi
Informatics Ph.D. Student, University of Illinois at Urbana-Champaign
Fei Yu
Fei Yu
Assistant Professor/Health Informatics Librarian, University of North Carolina at Chapel Hill
Mina Tari
Mina Tari
PhD Candidate, University of Washington

(291) Case study on COVID-19 and archivists’ information work

Keywords: Information behavior, information practice, archives, medical heritage collections

This paper presents preliminary findings from an exploratory, qualitative case study bounded by the city of Philadelphia. The case study brings the literature on information work (IW) to bear for the first time on archives and special collections repositories. Empirical interview data on archivists’ information work at five medical history collections, pre- and post- pandemic onset, suggests that institutional and personal conditions surrounding COVID-19 prompted archivists to change their information work tasks in phases, first shifting office tasks to remote work under quarantine, then to hybrid work contexts. We explore an information work model including work purposes, work tasks, and work roles. The model shows how tasks of collection management, reference services, and outreach constitute the context and purpose for archivists’ information work. The paper details how hybrid work tasks and hybrid work contexts emerged.

 

Garwood, Deborah A; Poole, Alex H

Drexel University, United States of America

 

(311) People’s Perceptions of AI Utilization in the Context of COVID-19

Keywords: Artificial intelligence, Coronavirus, Public perception, AI in healthcare, Interview research

Taking into consideration the scarcity of interview-based research in Artificial Intelligence (AI) literature, we conducted 15 semi-structured interviews regarding our participants’ experiences with AI, where we observed a number of notable themes. In this paper, we focused on participants’ thoughts and opinions of AI use during the novel coronavirus (COVID-19) pandemic, a global crisis. Although there have been studies relating AI to COVID-19, there is insufficient in-depth understanding concerning the way people feel about AI utilization in the context of COVID-19. While there was mostly positive feedback that AI could help in the COVID-19 calamity, such as COVID-19 testing and monitoring vital signs, two out of 15 participants expressed doubt that AI could be successfully implemented in healthcare, and four out of 15 participants mentioned potential is-sues with this AI application. We are among the first researchers exploring people's opinions on AI usage in the context of COVID-19, so this paper provides a foundation for future work.

 

Markazi, Daniela Mehri; Walters, Kristin Erika

University of Illinois at Urbana-Champaign, United States of America

 

(195) Comparison of Data Analytics Software Usage in Biomedical and Health Sciences Research: A Case Study

Keywords: Data Analytics Software, Biomedical and Health Sciences Research, Bibliometrics

Responding to the new data science initiative at the University of North Carolina at Chapel Hill (UNC-CH), this study aimed to investigate the usage of data analytics software (DAS) in biomedical and health sciences research. We selected three DAS tools (i.e., SAS, R, & Python), systematically searched PubMed and PubMed Central databases for UNC-CH publications in which any of the three tools was adopted, manually screened retrieved articles, and then conducted a bibliometric analysis. We found that (1) UNC researchers produced more publications using SAS than using R or Python. (2) The citation impact was similar across the publications supported by three tools and higher than the average of NIH-funded papers. (3) The most frequently addressed topics supported by SAS or R included cancer, HIV, risk factors and assessment, and associations between diseases/symptoms and clinical outcomes. Python was often used to investigate cancer genes and genetic inferences, interactions and sequencing. Overall, the prevalent adoption of SAS by UNC authors in biomedical research highlighted the importance of software availability, industry-academia collaboration, and training pro-grams. Our findings provided insights to the new data science initiative for informed decision making.

 

Yu, Fei; Mani, Nandita S.

University of North Carolina at Chapel Hill, United States of America

24/03/2021 18:00 +00:00 - 24/03/2021 19:30 +00:00
(24/03/2021 18:00 +00:00)
| Short Research Papers | 28 Attendees
Short Research Papers 10 (Short Research Papers)
Rebecca Noone
Rebecca Noone
Postdoctoral Fellow, University of Toronto
Wenyi Shang
Wenyi Shang
PhD student, School of Information Sciences, University of Illinois at Urbana-Champaign
Iris Xie
Iris Xie
Professor, University of Wisconsin Milwaukee
Nicole Simone Kuhn
Nicole Simone Kuhn
PhD Student, University of Washington

(465) Locating Embodied Forms of Urban Wayfinding: An Exploration

Keywords: urban wayfinding, embodied information practices, arts-based methods

The following short paper looks at the everyday information practice of ur-ban wayfinding in the context of pervasive locative media and mobile map-ping technology. The author asks: what informational cues are encoded in the urban landscape and activated through embodied practices of wayfind-ing? To explore this question of street-level wayfinding, the author utilizes the exploratory method of arts-based research, focusing on the act of giving directions, both spoken and drawn, and developing the research in four unique cities: Amsterdam, London, New York, and Toronto. Analysis of the data uses visual grounded theory and situational analysis. Based on the findings, the author classifies three types of urban forms that helped guide navigation during these wayfinding encounters: pathways, transmitters, and markings. In unpacking the variants within these registers of spatial sense-making, the author identifies informational elements of the city present in its material and built environment but also in its social and tacit forms. The paper offers a framework to look at the multiplicities of information, struc-tured and embodied, that guide wayfinding, situated beyond (but co-existent with) mobile mapping tools.

 

Noone, Rebecca

University of Toronto, Canada

 

(121) Improving Measures of Text Reuse in English Poetry: A TF–IDF Based Method

Keywords: Text reuse, TF–IDF, Method Evaluation, English poetry, Digital humanities

Text reuse measurement is important for both LIS and literary studies, where it is mainly used to study influence between authors. Although projects such as Tesserae have already adopted computational methods for investigating text reuse in Latin poetry, its potential applications to the rich collections of English poetry have not been realized. This research proposes a modified version of the Tesserae Project’s measure based on the insight embodied in TF–IDF to study English poetry. Using the Irish poet Yeats’ relationship to five English Romantic poets as a test case, three parallel experiments were conducted in order to evaluate the suitability of this method for English poetry. The results show that this new method is effective in measuring text reuse in English poetry, and the TF–IDF based modification is more sensitive to known cases of text reuse than the original method. This method can also be adopted to noncanonical literary works in the future, providing an example of the significance of LIS for digital humanities.

 

Shang, Wenyi (1); Underwood, Ted (1,2)

1: School of Information Sciences, University of Illinois at Urbana-Champaign

2: Department of English, University of Illinois at Urbana-Champaign

 

(119) Importance of digital library design guidelines to support blind and visually impaired users: Perceptions of key stakeholders

Keywords: Digital library design guidelines, Assessment, Blind and visually impaired users

This study was conducted to understand how key stakeholders perceive the im-portance of design guidelines that specifically target the needs of blind and visual-ly impaired (BVI) digital library (DL) users. An in-depth survey question-naire was distributed among 150 participants representing three stakeholder groups: BVI users, DL developers, and scholars/experts. Participants were in-formed about different help-seeking situations that BVI users encountered when interacting with a DL non-visually using screen reader assistive technology. They were then presented with a set of design guidelines to address each situation. Fi-nally, they were asked to rate the importance of each set of guidelines in remediat-ing the corresponding situation. Both quantitative analysis and qualitative analysis were applied to analyze the data. The results show that all key stakeholders agree it is critical to develop DL design guidelines to support BVI users. On one hand, the three groups share some similarities in rating the importance of guidelines for these help-seeking situations; on the other hand, the disparities mainly lie in the fact that DL developers and the scholars/experts focused more on the guidelines addressing the accessibility-related situations, while BVI users emphasized that DL design guidelines need to take into consideration both accessibility and usa-bility-related situations.

 

Xie, Iris (1); Babu, Rakesh (2); nWang, Shengang (1); Lee, Tae Hee (1); Lee, Hyun Seung (1)

1: Univ. of Wisconsin Milwaukee, United States of America

2: Envision

24/03/2021 20:30 +00:00 - 24/03/2021 22:00 +00:00
(24/03/2021 20:30 +00:00)
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Full Research Papers 8 (Full Research Papers)
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Alasdair Ekpenyong
Soo Hyeon Kim
Soo Hyeon Kim
Assistant Professor, Indiana University-Purdue University Indianapolis
Madelyn Rose Sanfilippo
Madelyn Rose Sanfilippo
Assistant Professor, School of Information Sciences, University of Illinois at Urbana-Champaign
Ryan O'Grady
Ryan O'Grady

(204) Digital Humanities Scholarship: A Model for Reimagining Knowledge Work in the 21st Century

Keywords: Digital humanities, knowledge production, knowledge work, post-industrial, postmodernism

The essay situates the academic subfield of the digital humanities (DH) as a notable example of late 20th century theories of knowledge (e.g. writings of Jean-François Lyotard and Fredric Jameson) that called for or predicted a shift from modern to postmodern cultures of knowledge work, knowledge organization, and knowledge production. The essay reviews DH as a case study of knowledge culture transitioning within the academic industry and suggests insights for how similar transitions may develop in other industries