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The iConference Awards recognize the most exceptional research papers and posters presented at the iConference each year. They are judged by the respective track chairs, in consultation with the conference and program chairs.

The winners will be announced at iConference 2023.

Doc Diss Award
Large Audience

Doctoral Dissertation Award

Winner, Runner-up, and Finalists

Click on the arrows to see all finalists in order of IDs.

(499) Leveraging Differential Privacy While Attending to Social and Political Commitments

Nitin Kohli

UC Berkeley School of Information

In this dissertation, we examine how differentially private algorithms can be used to compute statistics while attending to context specific social and political commitments. This inquiry is informed by three studies, each of which examines this question in distinct ways. In our first study, we consider ways to configure differentially private algorithms based on the privacy and accuracy concerns of data subjects and other stakeholders, while simultaneously attending to the values of privacy, fairness, and strategyproofness. Our second study considers how differentially private algorithms can be configured to attend to the context of public health, while providing policymakers with mobility statistics to inform decisions on lockdown mandates and other non-pharmaceutical interventions. Our third study examines how the absence of adequate information privacy protections create vulnerabilities that implicate decisional privacy in reproductive healthcare. Informed by these vulnerabilities, we provide guidance on how to safeguard these decisional privacy interests using a variety of mechanisms, including differential privacy. Throughout these studies, we develop theory and tools to effectively leverage differential privacy in practice. This work serves as guide for using mathematical approaches to attend to context specific social and political commitments in areas where statistical knowledge is essential to advancing the public good


Lee Dirks Award for Best Full Research Paper

Winner and Finalists

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(269) Research with User-Generated Book Review Data: Legal and Ethical Pitfalls and Contextualized Mitigations

Yuerong Hu, Glen Layne-Worthey, Alaine Martaus, J. Stephen Downie, Jana Diesner

University of Illinois Urbana-Champaign, United States of America

The growing quantity of user-generated book reviews has opened up unprecedented opportunities for empirical research on books, reading, and readership. While there is an abundance of literature addressing the legal and ethical use of user-generated and social media data in general, for user-generated book reviews, such discussions have been mostly absent. From a library and information sciences perspective, user-generated book reviews can pose novel challenges because each book reviewer may simultaneously be (1) a presumably anonymous and safe online user; and, (2) an identifiable reader who can suffer real harm, e.g., cyber doxing and personal attack. This user/reader duality can create conflicting recommendations regarding which legal or ethical guidelines to follow. According to our review, potential legal issues include copyright infringement and violations of terms of service/end-user license agreements and privacy rights, while ethical concerns are centered on users’ expectations, informed consent, and institutional reviews. This paper reviews (1) potential legal and ethical pitfalls in leveraging user-generated book reviews; and, (2) professional and scholarly references that might serve as useful guidelines to avoid or manage these pitfalls.

Best Full Paper
Image by Wan San Yip

Award for Best Short Research Paper

Winner and Finalists

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Best Short Paper

(156) Diversity measures for scientific collaborations

Ly Dinh¹, William C. Barley², Lauren Johnson², Brian F. Allan³

1: School of Information, University of South Florida, USA; 2: Department of Communication, University of Illinois at Urbana-Champaign, USA; 3: School of Integrative Biology, University of Illinois at Urbana-Champaign, USA

Diversity indices are widely used in many scientific disciplines to quantify the distribution of types within a dataset and are perhaps most strongly associated with the fields of ecology and economics. This paper synthesizes knowledge from four fields (ecology, economics, bibliometrics, team science) to show how diversity has been operationalized over time and to identify opportunities to advance studies of team diversity in team science research, a comparatively new and emerging field. In recent years, increasing efforts have been made to support interdisciplinary research teams and to better understand the relationship between interdisciplinarity and research outcomes through the lens of diversity measures. We find that diversity measures such as Shannon's and Simpson's indices have been prevalent proxies to capture the extent to which research teams comprise of interdisciplinary knowledge sources and perspectives. We also find that the ecological perspective of ``beta diversity'', an approach considering the relative differences between rather than within groups, offers compelling opportunities for teams and science of team science research. We describe the concept of beta diversity, and provide several examples of how a beta diversity perspective offers a lens to address research questions of interest to science of team science scholars.

Award for Best Poster

Winner and Finalists

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(377) Toxic By Design: Exploring the Relationship of Game Affordances and Negative Behavior

Ria Antony¹⁺⁴, Victoria Chang¹⁺², My-Thuan Huy Ha-Hoang¹⁺³, Julio C. Penaloza Refugio¹⁺⁵, Joe Eduard Valdez Rucker¹⁺², Ayse Gursoy¹⁺²

1: The iSchool Inclusion Institute (i3), University of Texas at Austin; 2: University of Texas at Austin; 3: University of California, Los Angeles; 4: University of Washington; 5: University of California, Irvine

Video games are a globally popular genre of entertainment. Online multiplayer games, in particular, include ways of interacting with players around the world. These ways of interacting can include space for negative, or “toxic behavior” that can significantly impact players who experience such behavior. This paper provides a preliminary literature review of the existing research on toxic behavior in online games. This paper outlines gaps in research in order to support the design of a future study of affordances in two popular online multiplayer games, League of Legends and Valorant. The literature review and context of inquiry offer initial steps towards a research project studying how to mitigate toxic behavior through design choices.

Best Poster
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