Reaction videos (RVs) are surging in popularity, emerging as a distinctive facet of participatory culture on modern social video-sharing platforms such as YouTube, TikTok, and Twitch. This study aims to explore not only the motivations and engagement patterns of viewers towards RVs, but also the underlying nature of the virality and community-building phenomena that this sub-genre of video content fosters. We conducted 16 semi-structured interviews with individuals who identified as regular viewers of reaction videos to gain a deeper understanding of how they discover reaction videos (RQ1), the values that drive their motivations for viewing RVs (RQ2), and the ways viewers engage with RVs (RQ3). Our research highlights the variety of original content that RVs utilize, ranging from movie trailers to music releases, and the different engagement strategies viewers rely on in their consumption of RVs. Our research highlights the wide range of original content that RVs engage with, from movie trailers to music releases, as well as the diverse engagement strategies viewers employ when consuming RVs. Our findings highlight the significance of emotional connections with reactors, the value of communal experiences centered on shared interests, and the role of RVs in facilitating content discovery and critique. Drawing on viewers’ experiences with RVs, this work offers a behind-the-scenes perspective on the complex dynamics of spectatorship and its influence on the production and consumption of content in today’s digital landscape. We further contribute to a nuanced and comprehensive understanding of reaction video culture.
As more people meet, interact, and socialize online, Social Virtual Reality (VR) emerges as a technology that bridges the gap between traditional face-to-face and online communication. Unlike traditional screen-based applications, Social VR provides immersive, spatial, and three-dimensional social interactions, making it a potential tool for enhancing remote collaborations. Despite the growing interest in Social VR, research on its role in collaboration remains fragmented, calling for a synthesis to identify research gaps and future directions. We conducted a 20-year scoping review, screening 2,035 articles and identifying 62 articles that addressed how Social VR has supported collaboration. Our analysis shows three key levels of support: Social VR can enhance individual perceptions and experiences within their groups, foster team dynamics with virtual elements that enable realistic interactions, and employ the unique affordances of VR to augment users’ spaces. We discuss how future research in Social VR should move beyond replicating physical-world interactions and explore how immersive environments can cultivate long-term collaboration, trust, and more diverse and inclusive participation. This review highlights the current practices and challenges, highlighting new opportunities for theorizing and designing Social VR systems that responsibly support remote collaborations.
This is a corrigendum for the article "Exploring Collaboration Patterns and Strategies in Human-AI Co-creation through the Lens of Agency: A Scoping Review of the Top-tier HCI Literature" published in Proc. ACM Hum-Comput. Interact. 9, 7, Article CSCW413 (November 2025), 43 pages.
Open Source Software for Social Good (OSS4SG), a specialized segment within the Open Source Software (OSS) domain, is gaining increasing recognition for its focus on addressing societal challenges and delivering positive social impact. Learning about how contributors engage with OSS4SG is crucial to its sustainability, as the long-term success of these projects relies heavily on active and ongoing contributor participation. However, no study has yet examined the dynamics of contributors within OSS4SG. To fill this gap, we analyzed over 2.2 million commits made by 5,860 contributors to both OSS4SG and general OSS projects on GitHub, identifying contribution patterns and factors influencing sustained contribution to OSS4SG. We found that although OSS4SG contributors tend to show lower overall contribution intensity and shorter active lifespans, their activity during engaged periods is relatively more regular compared to contributions to general OSS. In addition, contributors from developing regions (e.g., Africa) or women are more likely to start with and continue contributing to OSS4SG, despite their overall contribution levels being lower than those of others. Based on these insights, we propose targeted strategies to increase contributions to OSS4SG projects to maximize their social impact to benefit society and harness their potential to foster broader participation in open source, ultimately enhancing the sustainability of the whole community.
Small-scale and alternative farming is difficult, precarious work; most small farms in the United States survive less than ten years. Yet these food systems are an important site for developing sustainable, local, and justice-based practices that can impact many of the large challenges we face today. Building on rural HCI research in the CSCW community, this paper takes an autoethnographic approach to exploring undocumented economic systems between vendors at a farmers market in the United States. We draw on Tronto’s ethical qualities of care to understand the gifting and trading of labor, goods, knowledge, and emotional support between vendors. Based on these first-hand experiences, we offer research opportunities for HCI that could support caring economic systems in communities.
This paper presents a longitudinal case study of two volunteer-led computer clubs in Palestinian refugee camps in the West Bank. Combining participatory action research, autoethnography, and follow-up interviews conducted ten years later, we examine how socio-technical infrastructures of learning were built and sustained under intertwined constraints. While the clubs were designed to support children’s engagement with technology, the most meaningful outcomes were reported by the volunteers, whose roles required navigating logistical, interpersonal, and political challenges in resource-constrained settings. Our findings position volunteers as infrastructural actors: they stitched together tools, partnerships, and routines to stabilize the clubs and create a durable social infrastructure. We identify the breadth of work and social structures implicated in volunteering and show how technology mediates these interdependencies. Recognition and care practices (such as debriefs, reflection rituals, acknowledgments) emerge as design requirements for sustaining participation, reflecting a shift from questions of access to recognition observed in feminist hackerspaces. Gendered trajectories reveal how women volunteers negotiated leadership and gained professional capital in male‑dominated contexts. Our longitudinal findings provide an empirical account of an uneven temporality of impact: durable benefits accrue to those performing infrastructural labor (volunteers), whereas short‑term beneficiaries (child participants) recall little after a decade.
People are increasingly using Large Language Models (LLMs) for a sense of “localness,” yet their ability to accurately and equitably represent local knowledge remains unexamined. To investigate this, we conducted a large-scale evaluation using a benchmark of over 12,000 question-answer pairs spanning structured census data, local news, and social media. Our results show that performance is strongly shaped by data modality: structured tasks expose deep limitations in numerical reasoning and calibration, while open-ended prompts reveal a clear performance hierarchy favoring informal user-generated content over professionally edited prose. Our primary finding is the existence of deep, context-dependent disparities that affect communities differently. We uncover a dual geographic bias: in formal news contexts, models exhibit a strong “urban advantage,” leaving rural areas systematically underrepresented with lower semantic depth. Conversely, in social media data, models suffer an “urban penalty,” struggling to navigate the conversational complexity and slang of high-density areas. This indicates that while rural locales face a “poverty of data,” highly documented urban centers face a “poverty of precision.” We also identify a domain bias: models are more adept at handling concrete, physical questions but consistently struggle to capture the nuanced relational and cognitive dimensions of a community. This work provides the first systematic audit of localness disparities in LLMs, revealing how they reflect and risk amplifying real-world inequities. Achieving equitable local representation requires moving beyond passive evaluation to active intervention. We call for a concerted effort from the CSCW community to build richer and more ethical datasets, design interfaces that prioritize user verification over blind trust, and architect AI systems for deeper and more just engagement with place.
The rise of Generative AI (GenAI) has demonstrated significant potential to improve productivity and foster creativity among content creators, social media influencers with large audiences on platforms such as Instagram, TikTok, and YouTube. However, as GenAI tools became increasingly integrated into creative workflows, significant concerns have emerged about potential risks and harms, including misinformation, social biases, and threats to authenticity. While prior research in HCI and CSCW has documented the pressures content creators face within algorithmic ecosystems, relatively little is known about how creators practically manage responsibility work when using GenAI tools. To address this gap, we conducted semi-structured interviews (N = 16) with content creators active on popular social media platforms such as YouTube, Instagram, and TikTok, examining their motivations, practices, and specific challenges related to responsible GenAI use. Our findings reveal that creators’ motivations for practicing responsible AI use span personal reputation management, audience trust-building, and broader social responsibility. However, they face persistent tensions, as integrating GenAI significantly intensifies conflicts between responsible AI practices and the pressures of visibility, engagement, and monetization imposed by platform algorithms. Content creators are required to perform extensive and often invisible responsibility work, which directly conflicts with the rapid production cycles and engagement demands of algorithm-driven platforms. Based on these insights, we propose concrete socio-technical design implications at the individual, community, and institutional levels, advocating solutions that shift responsibility beyond individual creators alone.
Computer-supported cooperative work (CSCW) researchers have studied how teenagers experience safety risks such as cyberbullying and scam, but little attention has been paid to gambling. While teenagers’ access to traditional gambling, such as casinos, has been tightly regulated, internet technology has given rise to emergent forms of online gambling, which increasingly permeate teenagers’ everyday lives and exposes them to safety threats and gambling-related harm. Addressing this issue requires a deeper understanding of teenagers' risk perception of gambling, as it not only shapes individual decision-making but also influences societal behaviors and informs policies aimed at mitigating its harmful effects. To understand how teenagers perceive and deal with gambling risks, we analyzed how teenagers engaged in collective sensemaking of gambling in the r/teenagers subreddit, one of the largest online communities on Reddit for teenagers. Our findings revealed various gambling risks perceived by teenagers, the strategies they adopt to mitigate them, and the strong sense of agency they demonstrate in engaging with gambling-related content. Based on these findings, we propose gambling intervention recommendations targeting teenagers, as well as implications for platforms and policymaking.
This study investigates Shiksha Copilot, an AI-assisted lesson planning tool deployed in government schools across Karnataka, India. The system combined LLMs and human expertise through a structured process in which English and Kannada lesson plans were co-created by curators and AI; teachers then further customized these curated plans for their classrooms using their own expertise alongside AI support. Drawing on a large-scale mixed-methods study involving 1,043 teachers and 23 curators, we examine how educators collaborate with AI to generate context-sensitive lesson plans, assess the quality of AI-generated content, and analyze shifts in teaching practices within multilingual, low-resource environments. Our findings show that teachers used Shiksha Copilot both to meet administrative documentation needs and to support their teaching. The tool eased bureaucratic workload, reduced lesson planning time, and lowered teaching-related stress, while promoting a shift toward activity-based pedagogy. However, systemic challenges such as staffing shortages and administrative demands constrained broader pedagogical change. We frame these findings through the lenses of teacher-AI collaboration and communities of practice to examine the effective integration of AI tools in teaching. Finally, we propose design directions for future teacher-centered EdTech, particularly in multilingual and Global South contexts.
Through design workshops and ethnographic fieldwork, this manuscript explores how students in hybrid alternative high-schools navigate their conflicting desires for nurturing educational environments and efficient certification. We highlight two competing visions in students’ designs of future educational technologies: one of affirmative and supportive spaces that address student mental health, sense of community, and identity needs; another that prioritizes expediency through self-paced, on-demand learning. We make three key contributions: 1) documenting how students struggle to navigate competing educational purposes; 2) analyzing how current hybrid school structures meet and conflict with student desires; 3) demonstrating how design ideas originating from students embody these tensions, sometimes offering paths forward for creative reconciliation. We argue that hybrid schools represent a critical site for understanding the future of educational technology, and advocate for designing digital tools and platforms that balance care and efficiency while supporting diverse student needs in increasingly digitized educational landscapes.
Trust and transparency in civic decision-making processes, like neighborhood planning, are eroding as community members frequently report sending feedback “into a void” without understanding how, or whether, their input influences outcomes. To address this gap, we introduce Voice to Vision, a sociotechnical system that bridges community voices and planning outputs through a structured yet flexible data infrastructure and complementary interfaces for both community members and planners. Through a five-month iterative design process with 21 stakeholders and subsequent field evaluation involving 24 participants, we examine how this system facilitates shared understanding across the civic ecosystem. Our findings reveal that while planners value systematic sensemaking tools that find connections across diverse inputs, community members prioritize seeing themselves reflected in the process, discovering patterns within feedback, and observing the rigor behind decisions, while emphasizing the importance of actionable outcomes. We contribute insights into participatory design for civic contexts, a complete sociotechnical system with an interoperable data structure for civic decision-making, and empirical findings that inform how digital platforms can promote shared understanding among elected or appointed officials, planners, and community members by enhancing transparency and legitimacy.
While short video platforms such as TikTok, YouTube Shorts, and Instagram Reels are frequently criticised for facilitating the spread of misinformation, they are also increasingly leveraged as tools for countering it through debunking content. Although video-based corrections have demonstrated effectiveness, their persuasive impact may depend on the richness of their audio-visual elements. This study examines the persuasive efficacy of three fundamental presentation styles commonly used in short-form video content: (1) videos featuring only captions, (2) captions accompanied by relevant images, and (3) captions presented alongside the creator’s visible face. Our results indicate that videos incorporating either relevant and engaging imagery or the creator’s facial presence are significantly more persuasive than those relying solely on captions. Based on these findings, we propose practical recommendations for improving the effectiveness of debunking videos, with the aim of promoting belief revision and mitigating misinformation on short video platforms.
Technologies to support dementia caregivers are often oriented around key milestones and transitions in the caregiving journey, which may not align with how family caregivers conceptualize and adapt to the everyday realities of care. In this study, we present findings from semi-structured interviews with 15 family caregivers of people with dementia to understand how they perceive their caregiving journeys over time. We find that caregivers live in a constant state of flux, characterized by ongoing, unpredictable, and multidimensional changes and fluctuating care demands throughout their journey. Our findings identify three ways caregivers respond to this constant state of flux: navigating through interdependent, multidimensional changes; iteratively adjusting and abandoning tools and supports; and developing an anticipatory mindset oriented toward future disruptions. We contribute to CSCW and HCI by showing how ongoing, unpredictable fluctuations constitute dementia caregiving and use this orientation as a way of thinking about designing technologies for dementia care.
HCI technologies are increasingly used to promote the wellbeing of young people. While mental health professionals are significant resources to support young people in dealing with mental health challenges, little research has explored the distinctive perspectives between young people and professionals and how technology can be designed to navigate the tensions between them. To fill this gap, we conducted a two-stage study consisting of semi-structured interviews and a co-design workshop with university students and mental health professionals. Findings from the interviews revealed convergent and divergent perspectives between these two groups on the factors that motivate or discourage young people from seeking help from the professionals. In the workshop, insights of the interviews were further distilled into a set of card-based tools to facilitate shared understanding and collaboration between these two groups as they envisioned future technologies that address the interests and concerns of two groups. Our work contributes to ongoing discussions in HCI about how emerging technologies can be designed to promote shared understanding between these two groups and enable technology‑mediated mental healthcare tailored to individual needs and institutional contexts.
AI-powered technologies are becoming increasingly integral to children’s digital experiences through devices like interactive toys, home automation systems, and apps, offering rich, personalized, and dynamic interactions. Despite their growing prevalence, how these AI-powered platforms can be designed to address the unique needs of children remains largely underexplored. Leveraging family interactions with Smart Voice Assistants (VAs) as a case study, we aim to explore how to approach child-centered AI (CCAI) design from a family perspective in this work. Specifically, we interviewed 20 parents and observed children’s VA interactions in eight households in a non-Western context. Using the theoretical lenses of agency and family functioning, we provide empirical insights into family dynamics when interacting with VAs in a less studied cultural setting, such as variations in family interaction types around VAs, the autonomy exercised by different parties, and the family functional roles VAs played. Based on these findings, we argue that CCAI design should be understood as balancing children’s agency, the roles and goals of other involved actors, and the contexts in which AI is used, and that it should focus on creating AI technologies that support positive outcomes for children in ethical ways while thoughtfully considering other stakeholders and their varying purposes for engaging with AI. In doing so, we offer a reconceptualization of CCAI and point to design directions for AI technologies that more meaningfully center child users in family contexts.
This is a corrigendum for the article "Bridging the Technical Gap: A Unified Representation Framework for Voice-based Community Engagement Platforms" published in Proc. ACM Hum.-Comput. Interact. 9, 7, Article CSCW277 (November 2025), 39 pages.
This is a corrigendum for the article "Togedule: Scheduling Meetings with Large Language Models and Adaptive Representations of Group Availability" published in Proc. ACM Hum.-Comput. Interact. 9, 7, Article CSCW332 (November 2025), 24 pages (original DOI: https://doi.org/10.1145/3757513).
Informed consent is essential for ethical research, but applying it in technology research involving people with dementia can be challenging. We conducted interviews with researchers, participants with dementia, and data stewards to explore these challenges and strategies for obtaining consent. Using communication theory, we examined how linear, dynamic, and contextual communication elements influence consent practices. Our findings show that relying too much on one-way information transfer creates problems in conveying information, documenting agreements, monitoring ongoing consent, and improving the consent processes. However, dynamic, context-sensitive strategies, such as paraphrasing information, fostering personal relationships, and designing supportive environments, can turn consent into a collaborative and inclusive process. We offer practical recommendations and reflective questions to improve consent conversations in dementia research and suggest future directions for more dynamic consent materials. By reframing consent as a dynamic and contextual process, we aim to make technology research in sensitive settings more ethical and inclusive.
We are again thrilled to be able to present the Computer-Supported Cooperative Work and Social Computing (CSCW) community with an issue of the Proceedings of the ACM on Human-Computer Interaction, containing very interesting and relevant scholarship from its members. This issue includes 42 papers from the May 2025 cycle, selected from a total of 637 submissions and following two rounds of reviews and one revision. 209 submissions from this round will be further revised, reviewed again, and may appear in another issue of the journal later this year. Our external reviewers and track editorial board have together conducted a rigorous review process to select contributions of the highest quality advancing the CSCW field. As Track Chairs, we are grateful for the community’s collective efforts to continue shaping and sharing CSCW’s tradition of high-quality scholarship across the years.
