UMSI at CSCW 2026: Awards, Workshops and Papers
Friday, 10/09/2026
Last Updated: Friday, 10/09/2026
By Noor HindiThe 29th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) will be held October 10-14 in Salt Lake City, Utah. Several University of Michigan School of Information researchers will be presenting their work.
UMSI professor Cliff Lampe served as a publication chair for this year’s conference. Additionally, associate professor Sun Young Park served as a senior program committee member, and research fellow Yao Lyu and PhD candidate Jiyeon Amy Seo served on the poster program committee.
HONORABLE MENTION AWARDS
Jordan Taylor, Joel Mire, Alicia DeViro, Maarten Sap, Haiyi Zhu, Sarah Fox
Art-making is a collective social activity through which queer people engage in political resistance, develop identities, archive queer memory, and form community. However, in recent years, generative AI has disrupted queer artistic communities. Through 15 semi-structured interviews, we examine how queer artists are making sense of the encroachment of GenAI into their art worlds. Our findings surface significant tensions between the relationality of our participants’ queer art practices and the perceived anti-relationality of GenAI development and use. We detail how our participants refuse and resist GenAI use and development in response and highlight the limited role our participants saw for GenAI within art-making, such as the queer aesthetic potential of surreal image models. Drawing on queer theory, we discuss how CSCW researchers might support queer artists by refusing dominant AI imaginaries and supporting queer world-building.
PAPERS
Reporting Non-Consensual Intimate Imagery: An Audit Study of Deepfakes
Li Qiwei, Shihui Zhang, Andrew Timothy Kasper, Asia A. Eaton, Joshua Ashkinaze, Sarita Schoenebeck, Eric Gilbert
Non-consensual intimate imagery (NCII) inflicts significant harm. Currently, victim-survivors can use two mechanisms to report NCII online---as a non-consensual nudity violation or as copyright infringement. We conducted an audit study of takedown speed of NCII reported to X (formerly Twitter) of both mechanisms. We uploaded 50 AI-generated nude images and reported half under X's "non-consensual nudity'' reporting mechanism and half under its "copyright infringement'' mechanism. The copyright condition resulted in successful image removal within 25 hours for all images (100% removal rate), while non-consensual nudity reports resulted in no image removal for over three weeks (0% removal rate). We stress the need for targeted legislation to regulate NCII removal online and discuss ethical considerations for auditing NCII on social platforms.
The Aftermath of Technology-Mediated Scams: Strengthening Older Adults’ Efforts toward Redress
Sam Addison Ankenbauer, Robin Brewer
Technology-mediated scams are a pervasive and enduring form of digital harm affecting older adults. While prior research has largely emphasized prevention, awareness, and risk perception, comparatively little attention has been paid to what follows after a scam occurs. Conceptualizing the scam as an unfolding event, we argue that each stage of the scam—before, during, and after—is shaped by distinct sociotechnical arrangements and relational dynamics that demand tailored forms of analysis and intervention. Through a multi-method study, we examine the during and after, paying specific attention to the post-scam, during which older adults navigate the affective, social, and material aftermath of scams. In doing so, we extend HCI’s engagement with digital harm by articulating the post-scam as a critical site of coordination, redress, and justice-seeking, offering new directions for research and intervention.
"In-Parallel with Someone Else": Self-Employed Creative Careers Inspired by Social Media Influencers
Shanley Corvite, Matthew Kieran Prock, Julie Hui
Many social media influencers have achieved success through independent creative work, such as by monetizing content creation, obtaining brand deals, building businesses, and pursuing other self-made endeavors. Influencers often document their journey into independent creative work on social media platforms, including their successes and failures, which helps build empathy and trust with followers and is integral to building a successful brand. This social media content communicates aspects of self-employment, such as independence, hard work, and perseverance in the face of uncertainty and instability. These narratives may inspire viewers to also pursue self-employed creative work, which we investigated through the lens of entrepreneurial labor–the normalization and acceptance of risk for the freedom and autonomy associated and promised with independent work, typically in creative industries. We also examined the critical role social media platforms play in creative aspirants' entrepreneurial journey. Through semi-structured interviews with creative aspirants, we found that influencers can be motivational and inspirational, inform creatives' (online) business practices, and shape how creatives understand and embrace entrepreneurial labor. These processes were amplified by shared social identities as well as shared challenges of navigating social media platforms for creative work.
A Scoping Review of Queer Health & Well-Being Technology Research
Calvin A Liang, William W Liem, Daniel Delmonaco, Andrew B.L. Berry, Oliver Haimson, Kathryn Macapagal, Sean A. Munson
Technology has and will continue to have a significant impact on queer people’s health and well-being; however, it is not guaranteed that these implementations lead to meaningful advancements. Through a scoping review of 69 queer health technology papers in the ACM Digital Library, we review who queer health and well-being research has centered, what health topics have been targeted, and how technology has been used to address them. Our results identify trends in health foci and intervention implementation strategies, revealing opportunities for upstream efforts that work across individual, community, and structural levels. We therefore argue for greater attention towards structural constructions of queer health and well-being, specific and intentional groupings when developing interventions, and four commitments for designing and carrying out technology-enabled health interventions: commitments to holistic constructions of problem spaces, leverage points, and unintended harms; to reflexive practices for challenging assumptions; to accountability to community needs and flourishing; and to expansion towards situated and relational understandings of health. This work culminates in a framework and research agenda for queer health technology that provides guidance for future interventions.
Yuling Sun, Huiran Yi, Silvia Lindtner
The loss of meaning in life is increasingly prominent among many urban dwellers and white-collar workers. Recently, Lifestyle Entrepreneurship (LE) has emerged as a moral alternative approach to work that prioritizes personal meaning, self-expression, and sustainability over economic gain. While entrepreneurship has long been a CSCW focus, little attention has been paid to the distinct entrepreneurial work form. This paper investigates this rising LE phenomenon through a long-term ethnographic fieldwork in China. Our findings provide an empirical understanding of LE, spanning from LEers' motivations, self-identity, to their entrepreneurial practices and encountered challenges. Through these, we deeply discuss how LEers actively reconfigure work by deviating from productivity and efficiency toward values such as self-expression and meaningful living. LE, we argue, provides a critical site for rethinking what counts as work in digitally mediated societies, challenges its presumptions and goals by foregrounding an alternative mode of collaborative work that is value-oriented, deliberately small-scale, informal, and that blurs conventional boundaries between work and life.
Although many data scientists are eager to promote social justice, their efforts often fall short, and in some cases even exacerbate existing harms. This gap between intentions and impacts follows from issues in how data scientists conceptualize their role in social justice efforts. Data scientists typically presume a technician role, aiming to develop technical tools that will produce social justice. This default role generally results in depoliticized technofixes that do not lead to substantive changes. In this paper, we contribute a framework to guide data scientists in taking on more productive and equitable roles in social justice efforts. To develop this framework, we turn to movement lawyering, a practice within the law for situating lawyers in support of grassroots social movements. Based on our review of the movement lawyering literature, we propose a new approach for data scientists to support social justice, which we call ``movement data science.'' Movement data science suggests that data scientists should ground their efforts for social justice in sustained and solidaristic relationships with grassroots social movements. We provide a process to help data scientists build these relationships and identify roles to play within specific social justice efforts, based around four key practices. Although movement data science does not provide a simple blueprint for data scientists to follow, it can help them identify ways to support social justice beyond simply developing technical tools.
The Persistence of Retracted Papers on Wikipedia
Haoshan Shi, Yulin Yu, Daniel Romero, Emoke-Agnes Horvat
Wikipedia serves as a key infrastructure for public access to scientific knowledge, but it faces challenges in maintaining the credibility of cited sources—especially when scientific papers are retracted. This paper investigates how citations to retracted research are handled on English Wikipedia. We construct a novel dataset that integrates Wikipedia revision histories with metadata from Retraction Watch, Crossref, Altmetric, and OpenAlex, identifying 1,181 citations of retracted papers. We find that 71.6\% of the citations were initially problematic and in need of reader-facing repair, defined as those added before the paper's retraction (51.5\%) or introduced afterwards without proper warning (20.1\%). While many are eventually corrected, our analysis reveals that these citations persist for a median of 3.68 years (1,344 days). Through survival analysis, we find that bot-mediated flagging (RetractionBot), open access availability, pre-existing online visibility (e.g., Twitter/X mention counts), and page-level organization (e.g., number of categories on a Wikipedia page) are associated with a higher hazard of correction. Conversely, a paper's established scholarly authority—a higher academic citation count—is associated with a slower time to correction. Our findings highlight how the Wikipedia community supports collaborative maintenance but leaves gaps in citation-level repair. We contribute to CSCW research by advancing our understanding of this sociotechnical vulnerability, which takes the form of a community coordination challenge, and by offering design directions to support citation credibility at scale.
Suanmuanlian Tonsing, Michaelanne Thomas
This study examines how emergent roles enable marginalized Indigenous communities to strategically oscillate between social networking platforms during violent conflict. It responds to recent research in CSCW that recognizes the importance of platform-switching strategies and roles that enable broader publics to achieve political goals during conflict. To this, we contribute a typology of the emergent roles people assume that facilitate communication across online platforms under high-risk conditions, such as conflicts—particularly in Global South conflicts where digital resistance intersects with physical survival. In this article, we research the 2023 inter-Indigenous ethnic conflict in Manipur, where the Kuki and Zomi tribes were displaced and vilified as "illegal immigrants" by non-tribal Meitei groups on X (formerly Twitter). We found that WhatsApp functioned as a networked enclave for strategizing counter-narratives, while X served as a networked counterpublic space for delivering these resisting narratives. Two emergent roles on WhatsApp structured this oscillation: shepherding and gatekeeping. Shepherding equipped community members with the skills to engage effectively on X—despite limited prior platform familiarity—while gatekeeping ensured the enclave’s integrity by vetting participants and mitigating surveillance risks. These roles were dynamically adapted to crisis, adding to CSCW’s earlier models of social networking resistance during conflicts. By focusing on the emergent roles through oscillating across platforms, this study advances CSCW literature to understand the significance of paying attention to emergent roles that enable safety and resistance in contested digital spaces.
Post-Post-API Age: Studying Digital Platforms in Scant Data Access Times
Kayo Mimizuka, Megan A. Brown, Kai-Cheng Yang, Josephine Lukito
Over the past decade, data provided by digital platforms has informed substantial research in HCI to understand online human interaction and communication. Following the closure of major social media APIs that previously provided free access to large-scale data (the ``post-API age''), emerging data access programs required by the European Union's Digital Services Act (DSA) have sparked optimism about increased platform transparency and renewed opportunities for comprehensive research on digital platforms, leading to the ``post-post-API age.'' However, it remains unclear whether platforms provide adequate data access in practice. To address this question, we conducted a comprehensive survey of 119 researchers worldwide, followed by 19 in-depth interviews, to understand their experiences with data access in this new era. Our findings reveal significant challenges in accessing social media data, with researchers facing multiple barriers, including complex API application processes, difficulties obtaining credentials, and limited API usability. These challenges have exacerbated existing institutional, regional, and financial inequities in data access. Based on these insights, we provide actionable recommendations for platforms, researchers, and policymakers to foster more equitable and effective data access, while encouraging broader dialogue within the CSCW community around interdisciplinary and multi-stakeholder solutions.
PANELS/SIGs
Nazanin Andalibi, Oliver Haimson, Casey Fiesler, Marina Kogan, Megan Lane, Ufuoma Ovienmhada, Michaelanne Thomas
In this live play and academic panel, we examine what happens when AI arrives unexamined in contexts like healthcare and the workplace. We begin with a dramatic performance of AI Powder, a speculative fiction short story that questions what happens if we uncritically “just sprinkle some AI on it,” no matter what “it” is and what the consequences may be. We then hold a panel conversation integrating varying viewpoints about AI adoption and notions of AI inevitability. We discuss how techno-solutionism, technological somnambulism, and technological determinism make AI sprinkling appear inevitable and unremarkable despite vast consequences, and how the CSCW community can intervene.
How can we use "infrastructure" theory to study AI/ML applications?
Anya Martin, Yuchen Chen, Alex Jiahong Lu, Michaelanne Thomas, Charlotte Lee, Cindy Kaiying Lin
Artificial intelligence (AI/ML) has changed rapidly in definition over the last fifteen years, from platform algorithms to machine learning to the current (since 2023) focus on LLMs. However, throughout this period AI/ML methods have maintained a strong infrastructural center: AI/ML software (Pytorch, Tensorflow), compute (AWS, Microsoft Azure), and hardware (GPUs) are all closely tied to tech companies and their satellite institutions. NVIDIA maintains over a 70\% market share of "advanced AI chips" as of 2023, Meta and Google employees overwhelmingly resource the AI/ML packages PyTorch and Tensorflow, respectively, and Amazon (and to a lesser extent Google and Microsoft) maintain near-complete control over cloud computing infrastructures. As AI models and infrastructures reconfigure CSCW's classic workplace and community settings, we ask: how can infrastructure studies shed light on the growing monopolization of AI/ML training and application in computing infrastructures? How might this change CSCW understandings of infrastructure's role in supporting communities of practice and work? What can "infrastructure" apprehend about these AI/ML shifts, and what aspects of modern AI/ML might the framework struggle with?
POSTERS
Co-Designing Community-Centered AI Education for Adults: A Midwestern Case Study
Yao Lyu, Leonymae Aumentado, Holden Winton, Jared Lee Katzman, Sparkle Berry, Zachary E Rowe, Kimberly Sanders, Tawanna R Dillahunt
Artificial Intelligence (AI) education is increasingly important, yet adults outside higher education receive less attention. We report a case study of an AI education session with 54 adults (48 in-person and 6 virtual) in a predominantly African American community on the east side of a major Midwestern city. We ask: “What does AI education for adults outside formal educational systems look like in practice?” and “What does this AI education session reveal about AI literacy at the community level?” Through a co-designed session developed with community partners, we found that concerns about AI persisted but shifted to specific, locally grounded questions about AI design and deployment. We also discuss AI literacy from a community capacity perspective and argue for AI literacy frameworks grounded in local community contexts that strengthen community capacity.
Irene Yu, Gabriela Marcu
First-year international undergraduates from collectivistic cultural backgrounds navigate belonging across hybrid online and offline contexts as they transition into U.S. universities, yet existing work has underexplored how this process unfolds over time. We conducted semi-structured interviews with 13 participants, supported by journey mapping and descriptive survey measures. Findings show that belonging changed over time through three broad trajectories: gradual rising, relatively flat, and decline-to-recovery. Many students experienced an early belonging distress when friendly interactions did not develop into deeper friendship or group connection, and belonging recovered through repeated participation, peer and faculty support, cultural communities, and online-to-offline connection. Digital platforms supported belonging through rituals of care, relationship maintenance, and pathways into in-person communities, but did not replace face-to-face support. Our findings offer empirical insights on temporally responsive, culturally informed, and online-to-offline support for international student belonging.
Frontstage Mediation Work: Invisible Work Bridging Gaps Between AI Decisions and User Expectations
Yongjae Sohn, Daehyun Kwak, Jiyeon Amy Seo, Hyungjun Cho, Seongah Youn, Youn-kyung Lim
Automated service systems increasingly generate algorithmic operational decisions that shape how services are delivered. However, these decisions reach end-users only through frontline workers who carry them out in real-world settings. During this process, automated decisions can diverge from user expectations, surfacing as friction at the service encounter. We propose Frontstage Mediation Work as a preliminary analytic lens for examining the often invisible labor through which frontline workers anticipate and manage such misalignments between algorithmic decisions and user expectations. Drawing on a qualitative case study of an On-Demand Ride-Pooling service, we identify four recurring practices through which drivers sustain the service encounter when frictions arise. Such labor remains absorbed into routine operations, leaving no trace in performance metrics, system logs, or formal job descriptions. This paper contributes to worker-centered HCI scholarship by illustrating how automated services shift onto frontline workers the responsibility of managing the interactional consequences of system-level decisions.
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