Log in

Leading and Promoting the Information Field

Log in

2021 Awards


Lee Dirks Award for Best Full Research Paper

The Lee Dirks Award honors this friend and early supporter of the iConference. The winner recieves a $1,000 cash prize from Springer and the iSchools organization. 


Title: Data and Privacy in a Quasi-Public Space: Disney World as a Smart City (#357)

Authors: Madelyn Rose Sanfilippo, University of Illinois; Yan Shvartzshnaider, New York University

Abstract: Disney World has long been at the forefront of technological adoption. Walt Disney theme parks implement emerging technologies before other consumer or public spaces and innovates new uses for existing technologies. In contrast with public contexts with representative governance, Disney World is both an engaging prototype and a functioning quasi-public smart city, wherein a private actor controls ICT adoption and governance. As cities increasingly partner with private corporations in pursuit of smart systems, Disney provides a glimpse into the future of smart city practice. In this paper, we both explore normative perceptions of data handling practices within Walt Disney World and discuss contextual divergences from conventional cities. Implications consider what can be learned about privacy, surveillance, and innovation for other public applications, stressing the limitations of and potential social harms from Disney as a model for public services.


Title: How Asian Women’s Intersecting Identities Impact Experiences in Introductory Computing Courses (#382)

Authors: Mina Tari, University of Washington; Vivian Hua, University of Washington; Lauren Ng, University of Washington; Hala Annabi, University of Washington

Abstract: Asians are perceived as overrepresented in computing fields. However, understanding how intersecting identities complicates this view is essential. When considering gender, ethnicity, and socioeconomic class, it becomes clear Asians have varying experiences and representation within computing. Using critical race theory and feminist theory, our exploratory case study describes Asian women’s perceptions of inclusionary and exclusionary factors in their introductory computing courses as well as their undergraduate teaching assistants (TAs). We found that intersecting identities and context of the university change the salience of race for Asian women. Additionally, undergraduate TAs are seen as more relatable because of near-peer status, and their personalities more impactful than any identity characteristic.

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

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

Abstract: 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.

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

Authors: Zhentao Liang, Wuhan University; Fei Liu, Wuhan University; Jin Mao, Wuhan University; Kun Lu, University of Oklahoma

Abstract: 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.

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

Authors: Chelsea Kathleen Palmer, University of British Columbia; Christopher Rowell, University of British Columbia; Victoria L. Lemieux, University of British Columbia

Abstract: 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 of expertise. This tripartite paper first covers the origin and development of the theoretical three layer trust model for blockchain technologies, then discusses the pedagogical utility of this model within a virtual education setting, before describing the application of that learned model by one of the students 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 attempts to support the value of such theoretical models in establishing shared language for complex concepts across disciplinary divides. Finally, future research directions are suggested in order to establish greater validity for the concepts presented within this paper.

Best Short Research Paper Award


Title: Something New Versus Tried and True: Ensuring ‘Innovative’ AI Is ‘Good’ AI (#335)

Authors: Stephen C. Slota, University of Texas at Austin; Kenneth R. Fleischmann, University of Texas at Austin; Sherri R. Greenberg, University of Texas at Austin; Nitin Verma, University of Texas at Austin; Brenna Cummings, University of Texas at Austin; Lan Li, University of Texas at Austin; Chris Shenefiel, Cisco Systems

Abstract: What does it mean for AI to be innovative, and does new always mean better, particularly in terms of the ethical and societal implications of AI? This interview-driven study of 26 stakeholders of AI in the fields of technology development, law, and policy elucidates key tensions in producing innovative AI, as they are understood across sectors. As these stakeholders articulate a discourse on innovation, there is revealed a complex relationship between how innovative AI is conceived, both in terms of what is considered innovation, and how that innovation is seen to be restricted or supported through policy and regulatory action. Ultimately, this discourse operates on similar terms across these stakeholder groups, and presents a knotted, interlinked view of regulatory, design and policy concerns across the ecology of AI, from its data to its use.


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

Authors: Deborah A. Garwood, Drexel University; Alex H. Poole, Drexel University

Abstract: 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- pan-demic onset, suggests that institutional and personal conditions surround-ing 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 con-text and purpose for archivists’ information work. The paper details how hybrid work tasks and hybrid work contexts emerged.

Title: Creating Farmer Worker Records for Facilitating the Provision of Government Services: A Case from Sichuan Province, China (#315)

Authors: Linqing Ma, Renmin University of China; Ruohua Han, University of Illinois Urbana-Champaign

Abstract: Farmer workers constitute a unique social group in China. Due to the limitations of their rural hukous, they often cannot take full advantage of government services compared to urban hukou holders, and the lack of authoritative documentation on their basic information, skills, and employment histories creates more barriers to their access to public services. Government institutions have thus proposed to create records for farmer workers to better facilitate their service utilization, but only few such projects exist and more empirical research is necessary for understanding them. This paper presents an empirical case study of the Sichuan Province’s government digital repository for farmer worker records. Based on a qualitative analysis of public information and data collected on-site in Sichuan, the paper presents a detailed account of the background, development trajectory, and challenges of the repository project. The analysis of the case yields three insights. First, how the repository was built as part of a larger business system to support business needs enables the improvement of services and the enhancement of records for farmer workers to stimulate each other. Second, the case’s approach to responsibility allocation in farmer worker records management illustrates the advantages of having the human resources and social security department leading the project in terms of department-based allocation. However, its circumvention of the complexities of region-based allocation also created other challenges. Third, farmer worker records projects can be immensely labor-intensive, and securing robust, consistent government support is crucial.

Title: Development and Evaluation of a Digital Museum of a National Intangible Cultural Heritage from China (#400)

Authors: Xiao Hu, University of Hong Kong; Jeremy Tzi-Dong Ng, University of Hong Kong; Ruilun Liu, University of Hong Kong

Abstract: Intangible cultural heritage (ICH) such as traditional craftsmanship lacks a physical form and often originates from minority groups with little documentation. Digital technologies can be leveraged for documenting and archiving these assets of humanity. In particular, digital museums are established for promoting public understanding and appreciation of cultural heritage. Despite the richness of ICH in China, the development of digital museums of ICH is still in an early stage and from government endeavours. As part of an inter-disciplinary collaborative project involving academic researchers, in-formation professionals, and a private not-for-profit museum, this paper described the development of Gifts from Lanmama, a digital museum of Miao embroidery as a unique ICH from Guizhou ethnic minorities in China, and reported a preliminary evaluation of the digital museum with 78 users, in terms of its usability and affordance for learning about cultural heritage. Results revealed the strengths of the digital museum in terms of the rigor of metadata and its impact on improving users’ understanding and appreciation of Miao embroidery. Some issues and challenges were also identified, such as the lack of channels for user-system communication. These evaluation results offer insights for further improving the digital museum and also other end-user oriented digital presentations of similar ICH.

Title: Promoting Diversity, Equity, and Inclusion in Library and Information Science through Community-Based Learning (#444)

Author: Alex Poole, Drexel University

Abstract: This paper argues for the usefulness of Community-Based Learning (CBL) as a vehicle to promote demographic diversity, equity, and inclusion in Library and Information Science and iSchool education. First, we discuss our methodological approach, which is a qualitative case study. Next, we review the literature on diversity, experiential learning, and Community-Based Learning (CBL). Third, we unpack the ways in which one iSchool is implementing community-based learning in a novel way, namely by embracing data science and design thinking in its pedagogical approach to a new three courses as part of a twelve credit post-Baccalaureate certificate. We discuss the institutional context for the certificate, the project partners, the twelve CBL Fellows, and the curriculum, which includes two new courses (Design Thinking for Digital Community Service and Data Analytics for Community-Based Data and Service) and a capstone. We conclude by offering directions for future research.

Best Poster Award


ID# 536: Persuasion Strategies in Misinformation-containing Weibo Posts

Authors: Sijing Chen, Wuhan University; Lu Xiao, Syracuse University; Jin Mao, Wuhan University


Abstract: Social media users were found to be persuaded by misinformation and contribute to the propagation of misinformation. It is important and urgent to understand the mechanisms behind the presentation of misinformation-containing posts in social media. While previous research on online misinformation has focused on the non-content and surface-linguistic features, our study aims to explore sociological and psychological features from the perspective of persuasion strategies. Through content analysis based on the Aristotle's Rhetoric Theory, we found that the pa-thos is the most common act of persuasion in misinformation-containing posts. Furthermore, there are statistically significant relationships between the existence of some persuasion strategies and the retransmission of misinformation-containing posts. These findings enhance our understanding of the mechanisms behind misinformation-containing posts and shed lights on the development of computational misinformation detection and misinformation combating efforts.


ID# 640: Linguistic features and consumer credibility judgment of online health information

Authors: Jiaying Liu, Peking University; Shijie Song, Nanjing University; Yan Zhang, University of Texas at Austin


Abstract: General health consumers rely on different indicators to judge the credibility of online health information. However, it remains unclear how consumers perceive and interpret linguistic features regarding credibility on health-related webpages. To bridge the gap, this study investigated how consumers interpreted linguistic features and how these interpretations varied across different information sources by employing observation and interview methods with a sample consisted of 30 participants. The results suggested that consumers could perceive three main linguistics features: number of typos, use of jargons, and tone of speech. The linguistic features played significant roles in indicating different credibility levels during consumers’ judgment of commercial webpages. However, consumers relied less on linguistics features to judge the credibility of government and forum webpages. We discussed these main findings and proposed several implications and future research directions.

ID# 638: Perspectives of Deaf and Hard-of-Hearing Viewers on Live-TV Caption Quality

Authors: Akhter Al Amin, Rochester Institute of Technology; Matt Huenerfauth, Rochester Institute of Technology


Abstract: While the availability of captioned television programming has increased, the quality of captioning service is not always acceptable to Deaf and Hard of Hearing (DHH) viewers, especially for live or unscripted content, broadcast from local television stations. There is a need for formal metrics to evaluate captioning quality, to enable audits or quality assurance. Although some current caption-evaluation metrics focus on evaluating the textual accuracy (comparing the caption text and accurate transcription of what was spoken), there are other properties of captions that may influence the quality or usability judgments of DHH users. In this work-in-progress, we are conducting experiments with DHH participants to evaluate videos with various levels of caption quality, to learn which features correlate to user judgments. These studies will also yield a valuable dataset of videos with accompanying quality-judgments by DHH participants, which will be used to evaluate potential metrics we will design and evaluate.

ID# 581: Sustainability by design: Toward community-centered strategies for durable digital collections

Authors: Courtnie Thurston, University of Maryland, College Park; Katrina Fenlon, University of Maryland, College Park


Abstract: Thousands of digital humanities projects and digital community archiving initiatives have created diverse cultural heritage collections, which together constitute an extensive, scattered body of evidence of groups and histories that tend to be underrepresented in mainstream cultural institutions. Because they dwell outside of libraries and archives, these collections confront major barriers to sustainability. The vulnerability of community-centered digital collections compromises the completeness and equity of our collective digital memory. This poster presents a case study of one digital community archive, as part of an overarching investigation of community-centered strategies for sustaining digital collections over time. The Lakeland Digital Archive is an effort of the Lakeland Community Heritage Project to document a historic African American community by digitizing family records and gathering oral histories. This study aims to illuminate sustainability challenges and opportunities in the design and development of a digital community archive. The objectives of this research are to contribute conceptual and pragmatic guidance on community-centered sustainability, to promote dialog and collaboration among institutions and community collections, and ultimately to sustain a more diverse, distributed cultural record.

ID# 483: Writing Security: A Curriculum Intervention for Computer Security Ethics

Authors: Justin Petelka, University of Washington; Katie Shilton, University of Maryland; Megan Finn, University of Washington


Abstract: Security policies articulate and define behaviors, protocols, and relationships in security work. These documents also translate values, ideals, and biases into rules. Synthesizing research from studio-based pedagogy, public policy analysis, science and technology studies, and surveillance studies, this paper presents a course project to help information science students connect security policies with ethical concerns. This activity helps students identify structural considerations and consequences for indirect stakeholders, particularly traditionally disenfranchised groups. Our course activity walks students through a process of drafting, critiquing, and revising a security policy for one of three technology security contexts: COVID-19 contact tracing, network traffic monitoring, and remote exam proctoring technologies.

Best Chinese Paper Award 


ID#513: 大数据治理规则构成要素框架构想 (A components framework conception for big data governance rules)

Authors: Jie Huang and Xiaomi An, Renmin University of China 

Abstract: [Purpose/significance] 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.




Papers Publisher

Accepted papers will be published in Springer’s Lecture Notes in Computer Science


Keep up to date

By Email

Click here to receive iConference News & Updates via email. These include participation calls, deadline reminders, and program updates. We typically send no more than one message a month, and you can unsubscribe at any time. Sign up now.

By Social Media

Follow the iConference on

Follow us on

iSchools Inc.
2885 Sanford Ave. SW, Box 40576
Grandville, MI 49418

Powered by Wild Apricot Membership Software