Content Warning: This paper contains sexually explicit and violent images and text. User-created chatbots powered by generative AI offer new ways to share and interact with Not-Safe-For-Work (NSFW) content. However, little is known about the characteristics of these GenAI-based chatbots and their user interactions. Drawing on the functional theory of NSFW on social media, this study analyzes 376 NSFW chatbots and 307 public conversation sessions on FlowGPT. Findings identify four chatbot types: roleplay characters, story generators, image generators, and do-anything-now bots. AI Characters portraying fantasy personas and enabling hangout-style interactions are most common, often using explicit avatar images to invite engagement. Sexual, violent, and insulting content appears in both user prompts and chatbot outputs, with some chatbots generating explicit material even when users do not create erotic prompts. In sum, the NSFW experience on FlowGPT can be understood as a combination of virtual intimacy, sexual delusion, violent thought expression, and unsafe content acquisition. We conclude with implications for chatbot design, creator support, user safety, and content moderation.

AI companions enable deep emotional relationships by engaging a user’s sense of identity, but they also pose risks like unhealthy emotional dependence. Mitigating these risks requires first understanding the underlying process of identity construction and negotiation with AI companions. Focusing on Character.AI (C.AI), a popular AI companion, we conducted an LLM-assisted thematic analysis of 22,374 online discussions on its subreddit. Using Identity Negotiation Theory as an analytical lens, we identified a three-stage process: 1) five user motivations; 2) an identity negotiation process involving three communication expectations and four identity co-construction strategies; and 3) three emotional outcomes. Our findings surface the identity work users perform as both performers and directors to co-construct identities in negotiation with C.AI. This process takes place within a socio-emotional sandbox where users can experiment with social roles and express emotions without non-human partners. Finally, we offer design implications for emotionally supporting users while mitigating the risks.

Generative AI (GenAI) is both promising and challenging in supporting people with disabilities (PwDs) in creating stories about disability. GenAI can reduce barriers to media production and inspire the creativity of PwDs, but it may also introduce biases and imperfections that hinder its adoption for personal expression. In this research, we examine how nine PwD from a disability advocacy group used GenAI to create videos sharing their disability experiences. Grounded in digital storytelling theory, we explore the motivations, expression, and sharing of PwD-created GenAI story videos. We conclude with a framework of momentous depiction, which highlights four core affordances of GenAI that either facilitate or require improvements to better support disability storytelling: non-capturable depiction, identity concealment and representation, contextual realism and consistency, and emotional articulation. Based on this framework, we further discuss design implications for GenAI in relation to story completion, media formats, and corrective mechanisms.

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.

The design of user-generated content (UGC) platforms poses challenges in comprehensively addressing the ethical dimensions of recommendation algorithms and applying human-centered methods for their evaluation. This article presents a literature review of 97 studies on UGC algorithms (UGCAlgos) that incorporate human factors and user experience considerations to investigate the ethical issues explored in human-computer interaction (HCI) research. Our review identifies key themes in the ethical considerations surrounding UGCAlgos and the user modeling methods employed. We examine how common ethical concerns in recommender systems, such as content appropriateness, privacy, user engagement, transparency, fairness, and diversity, are studied and contextualized within UGC platforms. Furthermore, we summarize how these concerns are addressed through user modeling approaches, including data characterization, user context, user outsmarting, interface design, user beliefs, and community and societal impacts.

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 211 papers, of which 192 were accepted from the January 2024 cycle, and 19 were accepted from the July 2024 cycle. It reflects great efforts and contributions from external reviewers, Associate Chairs and Editors, who together have 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.

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 313 papers, of which 45 were accepted from the January 2024 cycle, 85 were accepted from the July 2025 cycle, and 183 were accepted from the October 2025 cycle. It reflects great efforts and contributions from external reviewers, Associate Chairs and Editors, who together have 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.

We are delighted to present this issue of the Proceedings of the ACM on Human-Computer Interaction to the Computer-Supported Cooperative Work and Social Computing (CSCW) community. The issue contains 171 papers, of which 117 were accepted from the July 2023 cycle, and 55 were accepted from the January 2024 cycle, and one was withdrawn. Exploring a broad range of inspiring and timely topics, the issue collects the sustained efforts of a community of authors, external reviewers, Associate Chairs, and Editors. The result is an outstanding selection of high-quality contributions which are certain to shape the future of the field. Our deepest gratitude as Papers Chairs goes to this community for its determination to extend the CSCW traditions of collegiality and rigor in crafting extraordinary scholarship.

Video-sharing platforms offer a unique avenue for people with disabilities (PWDs) to highlight their experiences, including the challenges and accessibility barriers they face. While creators with disabilities effectively use these platforms to share their life struggles and advocate for societal changes, the scope of research exploring the nature of the discourse activities related to disability challenges remains limited. Our study addresses this gap by conducting a comprehensive qualitative content analysis of 468 videos posted by YouTubers with a range of disabilities, including vision, speech, mobility, hearing, and cognitive and neural impairments. Our findings reveal a predominant discussion on stigma and lack of support. YouTube is also used to share difficulties related to communication and systemic problems. Creators with disabilities also share experiences with technologies and public and private environments, through which they discuss accessibility issues and solutions. Building on our analysis, we propose future research directions aimed at enhancing the experience and support for disability communities on video-sharing platforms.

Although multiple instance learning (MIL) methods are widely used for automatic tumor detection on whole slide images (WSI), they suffer from the extreme class imbalance WSIs containing small tumors where the tumor may include only a few isolated cells. For early detection, it is important that MIL algorithms can identify small tumors. Existing studies have attempted to address this issue using attention-based architectures and instance selection-based methodologies but have not produced significant improvements. This paper proposes cross-attention-based salient instance inference MIL (CASiiMIL), which involves a novel saliency-informed attention mechanism to identify small tumors (e.g., breast cancer lymph node micro-metastasis) on WSIs without needing any annotations. In addition to this new attention mechanism, we introduce a negative representation learning algorithm to facilitate the learning of saliency-informed attention weights for improved sensitivity on tumor WSIs. The proposed model outperforms the state-of-the-art MIL methods on two popular tumor metastasis detection datasets. The proposed approach demonstrates great cross-center generalizability, high accuracy in classifying WSIs with small tumor lesions, and excellent interpretability attributed to the saliency-informed attention weights. We expect that the proposed method will pave the way for training algorithms for early tumor detection on large datasets where acquiring fine-grained annotations is is not practical.

Video-sharing platforms (VSPs) such as YouTube, TikTok, and Twitch have grown rapidly in recent years and attracted millions of users. Research topics such as online communities, video interactions, and recommendation algorithms have drawn increasing attention. Group and community dynamics were also examined with live streaming and short-form videos. However, HCI literature lacks a holistic picture of video-sharing research themes, methods, and findings that summarizes the diverse topics on interaction modalities and communities. Prior reviews on VSPs were about a particular platform or reviewed as a part of social media. This paper contributes a scoping review of 106 articles on video-sharing published in HCI literature from 2012 to June 2022. We identified six research themes through grounded theory analysis and encoded five HCI research methods in VSP studies. We concluded a framework with five components to structure findings in video-sharing research, with which we reflect on future directions on this topic.

Video-sharing platforms such as Youtube are increasingly used by people with disabilities (PWDs) to share their experiences and concerns in their lives. However, there is no systematic examination of how and why YouTubers disclose their challenges publicly on YouTube. This poster presents a preliminary analysis of 257 video clips made by YouTubers with disabilities. The most common disclosed difficulties are related to social support and societal attitudes. PWDs also use YouTube to share knowledge about accessibility and advocate for public changes.

ASMR (Autonomous Sensory Meridian Response) has grown to immense popularity on YouTube and drawn HCI designers’ attention to its effects and applications in design. YouTube ASMR creators incorporate visual elements, sounds, motifs of touching and tasting, and other scenarios in multisensory video interactions to deliver enjoyable and relaxing experiences to their viewers. ASMRtists engage viewers by social, physical, and task attractions. Research has identified the benefits of ASMR in mental wellbeing. However, ASMR remains an understudied phenomenon in the HCI community, constraining designers’ ability to incorporate ASMR in video-based designs. This work annotates and analyzes the interaction modalities and parasocial attractions of 2663 videos to identify unique experiences. YouTube comment sections are also analyzed to compare viewers’ responses to different ASMR interactions. We find that ASMR videos are experiences of multimodal social connection, relaxing physical intimacy, and sensory-rich activity observation. Design implications are discussed to foster future ASMR-augmented video interactions.

Drug addiction has become one of the most severe worldwide social problems. Recent research has examined utilizing social media to support addiction recovery and the problematic use of social media for selling drugs and glamorizing drug use. Prior studies have focused on textual and networking-based social media such as Twitter, Facebook, and Reddit, but there is limited understanding of how video-based platforms like YouTube allow creators to share drug addiction-related videos and discourse about addiction problems. This work performs a content analysis of 387 drug-addiction-related videos collected from YouTube. The grounded-theory approach based on the health-emergency framework identifies how drug-addiction videos discourse the addiction-related risk, blame, urgency, praise, and solution. Video viewership and comments are also compared between the emerged video themes. Results suggest YouTubers educate others about drug addiction, disclose personal experiences, and advocate for addiction prevention and recovery. Based on our findings, we discuss the opportunities and challenges of using video-sharing to prevent and educate drug addiction.

Loneliness threatens public mental wellbeing during COVID-19. In response, YouTube creators participated in the #StayHome #WithMe movement (SHWM) and made myriad videos for people experiencing loneliness or boredom at home. User-shared videos generate parasocial attachment and virtual connectedness. However, there is limited knowledge of how creators contributed videos during disasters to provide social provisions as disaster-relief. Grounded on Weiss’s loneliness theory, this work analyzed 1488 SHWM videos to examine video sharing as a pathway to social provisions. Findings suggested that skill and knowledge sharing, entertaining arts, homelife activities, live chatting, and gameplay were the most popular video styles. YouTubers utilized parasocial relationships to form a space for staying away from the disaster. SHWM YouTubers provided friend-like, mentor-like, and family-like provisions through videos in different styles. Family-like provisions led to the highest overall viewer engagement. Based on the findings, design implications for supporting viewers’ mental wellbeing in disasters are discussed.

YouTube is not only a platform for content creators to share videos but also a virtual venue for hosting community activities, such as social media campaigns (SMCs). SMCs for public awareness is a growing and reoccurring phenomenon on YouTube, during which content creators make videos to engage their audience and raise awareness of global challenges. However, how the unique celebrity culture on YouTube affects collective actions is an underexplored area. This work examines an SMC on YouTube, #TeamTrees, initiated by a YouTube celebrity and sought to raise people's awareness of tree-planting and climate change. The authors annotated and analyzed 992 #TeamTrees videos to explore how YouTube celebrities, professionals, and amateurs in different channel topics diagnose problems, present solutions, and motivate actions. This study also looks into whether platform identities and framing activities affect campaign reach and engagement. Results suggest that #TeamTrees reached creators who are generally not active in social issues. The participating YouTubers were likely to motivate the viewers to donate and join celebrities' and community's actions, but less involved in examining the environmental problems. Celebrities' videos dominated the campaign's influence. Amateurs' videos had a higher engagement level, although they need more support to frame campaign activities. Based on these findings, we discuss design implications for video-sharing platforms to support future SMCs.

Multiple-display environments (MDEs) have promise in helping co-located sensemaking tasks by supporting searching, organizing, and discussion tasks. Co-located sensemaking occurs when two or more sensemakers forage for useful information within a dataset, creating and leveraging knowledge structures individually and together. Group territories in MDEs support communicating and assembling findings, but questions remain regarding how to best represent individual sensemaking efforts in the group territory to support the sensemaking collaboration. This paper empirically examines exploration of a large Twitter dataset using three group territory paradigms: parallel, connected, and merged. Results reveal that merging group work increases task complexity while separating individuals' sections in the group territory supports monitoring, and more interactions are performed when individual work is not connected in the group territory.

As the ubiquity of computers, computer-mediated communications (CMC) has evolved to satisfy one of humanity's basic needs - communication today. Text-based message exchanging has established itself as the most popular CMC medium in our lives than other modes of communication. Compared to face-to-face communication, CMC is not restricted in terms of time and place However, text-based communications lack much of the richness of contextual information. It has been argued that nonverbal cues such as emotions are effective in helping users understand the meaning and nature of the message. The aim of this paper is to use empirical evidence to gain insight in how different CMC interaction methods influence the sensing of emotions and how this embed breaks down emotion barriers between CMC users. We also report how emotion can affect different user groups in CMC.

Groupwork is core to the educational process at all levels, with peer learning activities demonstrated to be an important component in exploring new idea spaces. Recent advances in technology encourage a re-examination of ways that technology can support and expand groupwork. This paper examines how large multi-touch tabletop displays can be used by students in group information exploration, creation, and sharing situations. The multi-user, multi-touch features enable multiple people to transition between individual and group interactions with the display, rather than the turn-taking interactions common in older technologies. While this provides opportunities, it also presents challenges in the ways that activities for the shared space are crafted, executed, and evaluated. This paper describes how our software solutions encourage idea exchange, sharing, and awareness of the activities of others, toward crafting better artifact-centered educational experiences. Specifically, the paper describes three techniques for card-based explorations that help enable groupwork: semantic zoom, dynamic grouping and info glow. Semantic zoom considers how pinch zooming can vary not only artifact size but also artifact content, showing more information at larger sizes. Dynamic grouping features the card combination which facilitates idea generation and synthesization. Info glow highlights artifacts that have been recently accessed or changed, providing an enduring way to see modifications made by others. This paper explores usage of this environment and these techniques, focusing on their impacts on educational goals and objectives for K-8 and for undergraduates, to understand how students in pairs or triads work independently and together as they explore and create within information spaces. Results suggest that older students tend to engage more with each other, though students of all ages transition between quiet individual work and communicative group work. The techniques described in this paper inform ways that they can be configured to optimize idea exchange, sharing, and awareness, and ways that tools and classroom techniques can encourage a more dynamic and engaged learning environment.

Research suggests that different teaching styles and multiple exposures of different styles to material can aid in the learning process. While there are guidelines for identifying the best teaching style for material, new and evolving areas can present unique challenges. The emerging area of mobile software development, which combines aspects of software, hardware, and interpersonal interaction, captures many such challenges; e.g., understanding how to develop for multiple screen sizes, designing for GPS time lag, dealing with unreliable sensor data. Teaching these challenging materials seemed well suited for multiple approaches that leveraged different learning styles. This paper examines three teaching approaches employed in ten teaching modules across two semesters of a mobile software development course. The approaches included lectures, interactive tutorials, and Pair Programming. Lectures were used to introduce topics and explore underlying theories of development. The lectures included time for questions from and for the students, but otherwise did not have an active learning component. Two active learning approaches used in the class were interactive tutorials and Pair Programming. Interactive tutorials presented applied development approaches, then explored their use in an individual-based hands-on demos. Pair Programming is an agile software development practice, used in both industry and education, which enforces a role-based approach to learning new programming concepts. Homeworks were used to assess learning, and surveys reflected student satisfaction. Results show areas of promise and of concern with regard to the learning styles. It seems that repetition of topics is important for mastery of the topics. Foundational theories seem well suited for lectures, while programming concepts work better in active learning situations. Additional learning took place through office hours, online question forums, and individual and group online exploration. The findings suggest specific approaches to teaching challenging and unique mobile software development topics as well as a general approach to identifying ways to distribute learning objectives across lectures, interactive tutorials, and Pair Programming sessions.

Smartwatches are emerging as wrist-based computers capable of complex calculation and communication, and the computer science curriculum should reflect the challenges and opportunities that they provide in the education domain. This paper puts forth an experience report focused on efforts to incorporate smartwatches in an upper-level undergraduate mobile application development class during two academic terms. Lectures, in-class activities, homeworks, and projects were tailored toward providing rich design and implementation experiences for the students that engaged them in developing for the smartwatch and a paired mobile device. Our experiences highlighted how incorporating smartwatches into a mobile app development class adds a valuable dimension in terms of design and implementation challenges and allowed students to exercise some of the fundamental computer science topics.

This demo features smartwatch applications created by junior/senior CS students in a mobile development course. The course featured the Pebble smartwatch, with an e-ink display, vibrating motor, and accelerometer. Smartwatches enhance mobile device use by acting as a secondary display and providing immediate notifications, but designing for them has challenges in memory management, sensor programming, networking issues, and display size. Incorporating Pebble smartwatch development in a mobile app development class allowed students to exercise core computer science concepts to overcome Pebble hardware and software limitations and to develop applications that leverage Pebble affordances. Two sections of the class featured Pebble-focused assignments, including an open-ended homework, a focused homework, and a term design project coordinating smartphone-smartwatch use. The two-semester experience yielded apps in all Pebble-defined categories, including tools and utilities, notifications, remotes, health and fitness, and games. Examples of the students' work from each of the categories will be presented in this demo on topics such as music synthesizing, remote camera operation, course management alerts, and server management. The presented apps reflect student understanding of the sensor functionalities, hardware capabilities and limitations, and interactions of the phone-watch pair. This demo will serve as a valuable resource for those who plan to incorporate smartwatch development into their teaching practice. Based on the educational experience gleaned, future opportunities can explore the role of the smartwatch in mobile development and programming education for college and K-12 students.

Tongue-computer interaction techniques create a new pathway between the human and the computer, with particular utility for people with upper limb impairment. This study investigated the usability problems of camera-based tongue computer interface reflected through the user behavior and participants' feedback; specifically the exploration of referential techniques to make users aware of their tongue position and help adjust their gesture. Pros and cons of the referential strategies are discussed to foster future assistive tongue-computer interface design.

Using tongue to access computer for people with none or minimal upper limb function has been studied in recent years. These studies mainly focus on utilizing mechanical or electromagnetic devices. These devices, however, must contact to people's oral cavity and cause hygiene problems or accidental ingestion. This work presents an interaction technique named Tongible that employs tongue as input without any mechanical or electromagnetic assistive device. In Tongible, six gestures of tongue are captured by an RGB camera and used as basic controlling gestures. Preliminary usability testing suggests that Tongible is effective in pointing and text entry for people with dexterity impairment.