Xiaojuan Ma

Amateur badminton players increasingly record matches, yet existing tools provide only aggregate statistics or generic summaries, leaving most unable to extract tactical insights without expert guidance. A formative study (N=8) reveals the need for multi-granularity, video-anchored tactical analysis centered on rallies. We derive a taxonomy of performance issues from national-level athletes’ annotations and present TactiPlay, an interactive system that instantiates an expert-taxonomy-guided, rally-level, video-anchored review workflow. The system’s analytical pipeline organizes match events into taxonomy-grounded feedback, while its interface links structured reports to rally summaries, video evidence, and court visualizations. A within-subjects study (N=16) shows that TactiPlay elicits more frequent, concrete, actionable, and appropriate reflections than a report-and-statistics baseline. These findings show how organizing reviewed match evidence into a taxonomy-guided, video-linked workflow can support amateur players’ tactical reflection.

Reminiscence Therapy (RT), as a typical Non-pharmacological intervention (NPI), has become increasingly important in dementia care. While GenAI-powered tools have shown potential in enhancing RT, they often struggle with practical usability and effectiveness due to the complex and situated nature of real-world intervention processes. In this study, we conduct a three-stage, in-the-wild research, including a formative study with professional therapists, a therapist-involved iterative participatory design study, and an in-situ evaluation with key stakeholders, to explore how GenAI-powered tools can be effectively designed and used to support personalized, professional, and collaborative RT practices. Our findings reveal that while theory-driven tools can achieve technical and therapeutic effectiveness in the lab, the practical effectiveness is not solely determined by their theoretically grounded design, but emerges through role-stretched and negotiated use within distributed, multi-stakeholder care practices. Based on our findings, we propose a series of practical implications for future GenAI-powered intervention technologies.

AI-infused systems have demonstrated remarkable capabilities in addressing diverse human needs within online communities. Their widespread adoption has shaped user experiences and community dynamics at scale. However, designing such systems requires a clear understanding of user needs, careful design decisions, and robust evaluation. In this work, we present a systematic review of 77 studies on AI-infused systems in online communities, analyzing them through three lenses: the challenges they aim to address, their design functionalities, and the evaluation strategies employed. The first two dimensions are organized around four core aspects of community participation: contribution, consumption, mediation, and moderation. Our synthesis distills a set of key design lessons and considerations, including the necessity to design for broader community ecosystems and prioritize user emotional experiences. We conclude by outlining future directions, such as newcomer socialization and inclusive design.

Critical news reading (CNR), which requires grasping the holistic ideas of and raising critical thoughts on the news, is beneficial yet challenging for general people who usually get information on daily social media. Comments under the news can aid CNR by providing complementary information and other readers’ diverse and critical thoughts. However, it is under-investigated how to leverage these comments to support users in CNR. In this paper, we first derive user requirements for a comment-based CNR tool from literature and a formative study (N=12). Then, we develop CoNewsReader , a comment-based interactive CNR tool powered by a large language model. CoNewsReader supports users in grasping the news idea with complementary information from comments, filtering useful comments for CNR, and getting questions generated based on the comments to conduct critical thinking. Our within-subjects study with 24 university students indicates that compared to a baseline news reading interface in social media, participants with CoNewsReader have a more engaging CNR experience and perform better on comprehending the news and raising critical thoughts. We discuss design considerations for supporting reading tasks with user- and machine-generated content.

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 contains a further 152 papers from the May 2025 cycle, building on the 42 papers that were originally accepted in this cycle and published earlier this year in the second issue of PACMHCI volume 10. The papers in this issue were selected from 209 submissions that were offered the option to revise and resubmit after two previous rounds of review in November 2025. 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.