Teenagers are avid users of Discord, a fast-growing platform for synchronous communication where they often interact with strangers. Because Discord combines private DMs, semi-private voice channels, and public servers in one place, it creates a hybrid environment that can produce complex—and underexplored—safety risks for teenagers. Drawing on 16 interviews with teenage Discord users, this study examines their strategies for navigating risky social interactions in the platform. Our findings reveal that when teenagers encounter risks during social interactions, they exercise vigilance by evaluating suspicious interactions before forming friendships, using safety tools, and engaging in controlled risk-taking to safeguard their privacy and security. At the community level, they mitigate risks through selective participation in servers, a practice supported by vigilant governance structures. We discuss how vigilance enables teenagers to act during risky encounters to protect themselves, advancing understanding of teenagers’ agency in risk navigation and informing teen-centered designs for safer online environments.

Large language models (LLMs) are increasingly integrated into daily life through conversational interfaces, processing user data via natural language inputs and exhibiting advanced reasoning capabilities, which raises new concerns about user control over privacy. While much research has focused on potential privacy risks, less attention has been paid to the data control mechanisms these platforms provide. This study examines six conversational LLM platforms, analyzing how they define and implement features for users to access, edit, delete, and share data. Our analysis reveals an emerging paradigm of data control in conversational LLM platforms, where user data is generated and derived through interaction itself, natural language enables flexible yet often ambiguous control, and multi-user interactions with shared data raise questions of co-ownership and governance. Based on these findings, we offer practical insights for platform developers, policymakers, and researchers to design more effective and usable privacy controls in LLM-powered conversational interactions.

With the development of consumer surveillance technologies, monitoring has become increasingly accessible and woven into family life. Prior work has examined parents’ attitudes, privacy concerns, and selected uses of surveillance technologies like smart cameras and location-tracking apps, but offers limited accounts of how parents, as surveillants, configure and experience these technologies themselves in daily parenting. We address this gap by focusing on baby monitoring technologies (BMTs) as a high-salience context during a sensitive stage of family life. Using inductive thematic analysis of Reddit discussions, we examine how parents engage with BMTs in practice. Our findings revealed how parents actively assemble and configure BMTs, navigate and manage their emotions through them, negotiate privacy frictions and boundaries, and safeguard security in their use of such technologies within parenting and caregiving. We conclude by discussing implications for surveillance research and design for monitoring technologies in care.

Gaming is a meaningful part of children’s lives, yet its safety has drawn increasing concerns from scholars and the public. On platforms like Roblox, children may encounter extremist roleplay, scams, or virtual rape. Prior research has emphasized technical interventions that address risks after they occur and ethical frameworks for game design, but children’s perspectives on safety design remain missing. To address this gap, we conducted a cooperative inquiry study to co-design safety mechanisms with 22 children aged 7–12. Children proposed designs emphasizing transparent information about games and purchases, community accountability through reporting and reviews, player empowerment to manage social boundaries and engagement, and age-appropriate game navigation. Our findings extend safety-by-design research by foregrounding children’s perspectives, showing how they envision safety mechanisms across both game and platform design, while enjoying safe play through risk exposure, allocating trust, and balancing platform support with agency.

Abstract The smooth functioning of the gig economy relies on gig workers’ local execution of tasks assigned by global platforms like Uber. Within this broader workforce, gig drivers (e.g., rideshare and delivery workers) draw on their local knowledge – information and skills specific to a particular region – to navigate and optimize routes. Building on a substantial body of research on gig work, this study turns attention to how gig drivers develop and deploy knowledge practices within the gig economy infrastructure. To address this, we analyzed 25 semi-structured interviews, revealing how drivers’ knowledge practices enable them to adapt platform systems to local conditions, develop algorithmic-local knowledge by integrating insights about platform behavior and market dynamics, and strategically regulate knowledge exchange with peers. We discuss how such knowledge practices play a critical role in localizing platform work, bridging the gaps between gig platforms’ global standards and local conditions.

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.

The HCI community has been actively developing and studying the use of Personal Informatics (PI) systems.While celebrating the headways, researchers have uncovered many unintended consequences of using PI systems, such as data-induced stress and obsessive tracking, but there has been a lack of systematic analysis of these consequences and their underlying causes.In this work, we reviewed 172 PI research articles, highlighting that tracking and interacting with personal data can adversely affect individuals' cognitive load, emotional well-being, social acts, and behaviors, while bringing practical challenges.By synthesizing the pathways through which these consequences occur, we recognized issues in the data-centric design ideology, variations across tracking needs and literacy, the evolving social dynamics, and individuals' intention-behavior gap.Reflecting on the findings, we discuss how to best leverage personal data in our lives and propose a practice-oriented research agenda to mitigate these unintended consequences.

User-generated game (UGG) platforms such as Roblox have become increasingly popular among children but are also criticized for hosting rampant online risks, such as virtual gang rape and spread of extremist ideologies. However, limited research has explored the risks from child players’ perspectives. Through an interview study with 26 child players, we found three categories of risks: varied scams, the normalization of anti-social behaviors, and adult roleplays. We also identified three types of safety practices child players employed on UGG platforms: adaptive safety practices across different social relationships, applying heuristics to safeguard their safety, and tinkering with safety features. We discuss design-mediated risks in UGGs targeting vulnerable child players and challenges and opportunities for risk mitigation strategies in UGGs. Lastly, we provide design implications for UGG platforms to support child players and provide a safe place for them to play.

User-generated game (UGG) platforms like Roblox are enormously popular among children but are increasingly scrutinized for safety risks, such as gambling-like gameplay features and disturbing game themes such as slavery and Nazi roleplay. Researchers have started to examine harms in UGGs, but little attention has been paid to how game creators themselves consider child safety in their game making practices. To answer this question, we conducted an interview study with 20 Roblox creators with varied degrees of success. We found that our interviewees observed several types of risks to child players’ safety in their games, such as child-specific deceptive design, gambling-like gameplay, sexual abuse, and scamming. They further reasoned about major causes of these safety risks, such as Roblox's profit-driven monetization model, and leaving the burden of moderation to individual game creators. We discuss implications for platform governance on UGG platforms as well as policymaking.

Personally identifiable information (PII) is a fundamental concept in privacy research and regulations. Understanding users' perspectives on PII is critical, as their understanding of PII can significantly affect their privacy decisions and practices. While much research has explored users’ privacy perceptions and disclosure preferences regarding PII, less attention has been focused on how users internally define and conceptualize PII. In this study, we conducted interviews with 32 participants to investigate their conceptualization and understanding of PII, using period and fertility tracking apps as the context. Our findings reveal how users perceive the processes and contexts through which personal information, by becoming identifiable, transitions into PII, as well as concerns about data sharing and misuse in these apps. We conclude by advocating for addressing the misalignment between users' perceptions of PII and the regulatory protections and privacy designs surrounding it.

Personalized support is essential to fulfill individuals' emotional needs and sustain their mental well-being. Large language models (LLMs), with great customization flexibility, hold promises to enable individuals to create their own emotional support agents. In this work, we developed ChatLab, where users could construct LLM-powered chatbots with additional interaction features including voices and avatars. Using a Research through Design approach, we conducted a week-long field study followed by interviews and design activities (N = 22), which uncovered how participants created diverse chatbot personas for emotional reliance, confronting stressors, connecting to intellectual discourse, reflecting mirrored selves, etc. We found that participants actively enriched the personas they constructed, shaping the dynamics between themselves and the chatbot to foster open and honest conversations. They also suggested other customizable features, such as integrating online activities and adjustable memory settings. Based on these findings, we discuss opportunities for enhancing personalized emotional support through emerging AI technologies.

Abstract Video games have been a unique study context for computer-supported cooperative work (CSCW) researchers for decades. However, despite their collaborative richness, CSCW has not yet developed a systematic understanding of video games as a site for studying cooperation and social interaction—limiting its ability to engage with the increasingly social, digital, and playful nature of work. Particularly, what are the academic characteristics of video game studies? What topics are studied in the context of video games? And what are the unique facets of the video game context? To answer these questions, we conducted a systematic literature review by analyzing 67 studies of video games published in CSCW outlets between 1998 and 2023. We describe these studies’ academic characteristics and the topics studied in the context of video games through seven themes. We further identify six unique facets of collaborative work that scholars gain through game studies. We conclude that video games not only serve as an empirically rich site for examining and enriching existing CSCW theories and frameworks, but also constitute unique and oftentimes novel sociotechnical configurations that recontextualize CSCW. We further point to gaps, opportunities, and future directions for CSCW researchers interested in exploring the diverse social and collaborative dynamics in games, thus contributing to a more inclusive and expansive understanding of collaboration in digitally mediated environments.

Large language models (LLMs) could extend AI support for mental well-being with their unprecedented language understanding and generation ability. While we have seen individuals who lack access to professional care utilizing LLMs for mental health support, it is unclear how they prompt and interact with LLMs given their individualized emotional needs and life situations. In this work, we analyzed 49 threads and 7,538 comments on Reddit, aiming to understand how people seek mental health support from GPT by creating and crafting various prompts. Despite GPT explicitly disclaiming that it is not an alternative to professional care, we found that users continued to use it for support and devised different prompts to bypass the safety guardrails. Meanwhile, users actively refined and shared their prompts to make GPT more human-like by specifying nuanced communication styles and cultivating in-depth discussions. They also came up with several strategies to make GPT communicate more efficiently to enrich the customized personas on the fly or gain multiple perspectives. Reflecting on these findings, we discuss the tensions associated with using LLMs for mental health support and the implications for designing safer and more empowering human-LLM interactions.

Women’s participation in competitive gaming continues to grow. Despite growing attention to women’s presence and challenges in gaming, research has largely overlooked their unique experiences with toxicity in competitive environments. Our study addresses this gap by examining the perspectives of 28 women who play competitive games at varying levels. Through reflexive thematic analysis of semi-structured interviews, we discovered how women are being harmed by gendered toxicity and desire for justice. We present two key findings: 1) the forms of gendered toxicity women perceive in competitive gaming and 2) how women respond to their experiences with gendered toxicity. Using women-centered perspectives, our research deepens the understanding of how gendered toxicity marginalizes women and highlights confrontational strategies that seek justice and drive change. We demonstrate that gendered toxicity sustains a sexist meritocracy and exposes the limitations of existing interventions and mitigation strategies. Our findings encourage game developers and industry practitioners to design more inclusive moderation systems and competitive gaming events.

Fake games are an emerging form of games characterized by misleading advertising (external referent) and perceived inauthenticity in gameplay (internal referent). While previous research has examined game authenticity, deceptive advertising, and game design, there is a lack of understanding about why players engage with fake games despite their deceptive nature and how they cope with the fakeness of these games. To address these questions, we conducted an interview study with 30 mobile game players. Through reflexive thematic analysis, we identified four motivations for playing fake games, such as curiosity and easy entertainment, and four coping mechanisms, including adaptive and reconciled play. We discuss how players uniquely interact with the fakeness of fake games and how these games form a distinct ecosystem at the intersection of digital platforms, digital marketplaces, and game developers. We conclude with implications for research and design to mitigate their impact and improve the gaming environment.

Predatory monetization in video games refers to purchasing systems that hide or postpone the complete financial consequences until players are already deeply committed, both financially and emotionally. These systems manipulate players into spending against their genuine interests, benefiting game companies while causing potential financial harm. This issue has drawn increasing scholarly and societal attention, but little research has explored how players perceive the influence of predatory monetization on their gaming experiences. Through an interview study with 23 players of popular user-generated games hosted on platforms such as Roblox and Minecraft and a reflexive thematic analysis, we identified three key influences of predatory monetization: felt manipulation, monetized interpersonal relationships, and risks with mitigation strategies. We further describe social monetization, where monetization and players’ social experiences are closely intertwined, as well as the ecosystem of predatory monetization, where multiple stakeholders play interconnected roles in enabling and sustaining predatory monetization practices. Finally, we offer design implications for mitigating the negative influences of predatory monetization.

Metaverse platforms have been on the rise in recent years, offering three-dimensional (3D), immersive virtual worlds while encouraging user-generated content (UGC) in various forms. Roblox, a popular metaverse platform, enables its users to create a holistic virtual world (i.e., develop a 3D game) for other users to interact with. However, complex UGC is also challenging to moderate. Roblox has been notorious for its users’ harmful designs, such as Nazi or terrorist role-playing mechanisms. In this study, we explore how harmful design takes place on Roblox. Through a grounded theory analysis of the ‘r/Robloxgamedev’ subreddit, we conceptualize an ecological view of harmful design, foregrounding three interconnected circumstances, namely sociotechnical risks, socioeconomic precarities, and normative (in)sensitivities, which work together to condition and give rise to harmful designs and bring about unique governance challenges to metaverse platforms. We conclude by laying out implications for design moderation.

Protecting children’s online privacy is paramount. Online platforms seek to enhance child privacy protection by implementing new classification systems into their content moderation practices. One prominent example is YouTube’s “made for kids” (MFK) classification. However, traditional content moderation focuses on managing content rather than users’ privacy; little is known about how users experience these classification systems. Thematically analyzing online discussions about YouTube’s MFK classification system, we present a case study on content creators’ and consumers’ experiences. We found that creators and consumers perceived MFK classification as misaligned with their actual practices, creators encountered unexpected consequences of practicing labeling, and creators and consumers identified MFK classification’s intersections with other platform designs. Our findings shed light on an interwoven network of multiple classification systems that extends the original focus on child privacy to encompass broader child safety issues; these insights contribute to the design principles of child-centered safety within this intricate network.

Tracking is inherent in and central to the gig economy. Platforms track gig workers’ performance through metrics such as acceptance rate and punctuality, while gig workers themselves engage in self-tracking. Although prior research has extensively examined how gig platforms track workers through metrics – with some studies briefly acknowledging the phenomenon of self-tracking among workers – there is a dearth of studies that explore how and why gig workers track themselves. To address this, we conducted 25 semi-structured interviews, revealing how gig workers self-track to manage accountabilities to themselves and external entities across three identities: the holistic self, the entrepreneurial self, and the platformized self. We connect our findings to neoliberalism, through which we contextualize gig workers’ self-accountability and the invisible labor of self-tracking. We further discuss how self-tracking mitigates information and power asymmetries in gig work and offer design implications to support gig workers’ multi-dimensional self-tracking.

Financial trading has become commonplace, involving the purchase and sale of securities such as stocks and bonds. While HCI research has investigated people’s financial literacy and decision-making and how to design for it, little is known as to how people form financial conversations on social media. To answer this question, we used a grounded theory approach to analyzing financial conversations in the YOLO (‘you only live once’) posts on the r/WallStreetBets subreddit (WSB), one of today’s largest financial online communities. We describe how WSB’s discursive culture portrays its gambling-like, high-risk trading by likening trading to gambling, celebrating it, and normalizing financial risk-taking. We discuss the rise of social investing, including how individual investors’ affective relationships encourage their outsized risk-taking, as well as reflect on its looming financial risks, especially to already marginalized groups. Lastly, we propose implications for design and policymaking.

Moderation systems of online games often follow a retributive model inspired by real-world criminal justice, expecting that punishments can help users to reform behavior. However, decades of criminological research show that punishments alone do not work and call for a rehabilitative approach, such as community-based rehabilitation (CBR), to help offenders transform their minds and behavioral patterns. Motivated by this call, we explore how moderated users view punishments in a community context and how other community members respond in League of Legends (LoL), one of the largest online games. Specifically, we focus on how peer support is sought and provided on the /r/LeagueOfLegends subreddit, the largest LoL-related online community. Our content analysis of player discussions characterized the communication between moderated users and peers as informative, constructive, and reflexive. We highlight the importance of involving community in moderation systems and discuss implications for designing CBR mechanisms that could enhance moderation systems.

After the overturn of Roe v. Wade gave states the license to ban abortion, numerous people in US have grown to worry about privacy in using period and fertility tracking apps. To address these concerns, some app companies have issued public statements to engage in privacy communication with their users. Prior literature has investigated period and fertility tracking apps’ data practices in their privacy policies. However, there remains a dearth of knowledge regarding how companies use privacy communication to address historic privacy-related events such as the overturn. To address the gap, this study investigated app companies’ public statements addressing the overturn of Roe using a combined approach of thematic and discourse analysis. Our findings revealed that companies strategically emphasize their commitment to privacy by demonstrating how their business practices and values are closely intertwined with their efforts to protect user data. We conclude by discussing translatable implications for privacy research.

On June 24, 2022, the U.S. Supreme Court overturned Roe v. Wade, which has led to full bans on most abortions in 14 states within one year. Many people in the U.S. use period and fertility tracking apps for reproductive healthcare and concerns have arisen about the privacy risks these apps might pose in the wake of Roe reversal. Existing literature on privacy risks of period and fertility tracking apps has primarily examined the privacy policies and practices of these apps. However, how users make sense of the privacy risks of these apps, especially in the post-Roe time, remains understudied. This study explores collective privacy sensemaking on social media, a practice in which people collectively make sense of a privacy situation. Our findings reveal how people contextualize privacy issues, speculate about the associated risks, as well as explore risk mitigation strategies. We conclude with privacy design implications for privacy design in period and fertility tracking apps and contribute insights that could inform policymaking and legal perspectives.

An increasing number of game platforms, such as Roblox, enable game creators to develop user-generated games (UGGs). Yet, these platforms often come under scrutiny for hosting UGGs that contain harmful content, ranging from sexually explicit material to Nazi-themed roleplay. Limited attention has been paid to how harmful UGGs are ideated by game creators. To address this question, we studied an online Roblox creator community, where Roblox creators collectively engage in design ideation to brainstorm design ideas for UGGs. Through an inductive thematic analysis, we found three primary ways where Roblox creators' design ideation becomes risky, including how Roblox creators generate risky game design ideas, navigate through policy boundaries to develop these ideas, and share strategies of bypassing moderation. Based on our findings, we discuss ethical and governance challenges facing user-generated games. We propose design implications to support game creators in developing ethical game design ideas and safe game designs.

Metaverse platforms such as Roblox have become increasingly popular and profitable through a business model that relies on their end users to create and interact with user-generated virtual worlds (UGVWs). However, UGVWs are difficult to moderate, because game design is inherently more complex than static content such as text and images; and Roblox, a game platform targeted primarily at child players, is notorious for harmful user-generated game such as Nazi roleplay games and gambling-like mechanisms. To develop a better understanding of how harmful design is embedded in UGVWs, we conducted an empirical study to understand Roblox users’ experiences with harmful design. We identified several primary ways in which user-generated game designs can be harmful, ranging from directly injecting inappropriate content into the virtual environment of UGVWs to embedding problematic incentive mechanisms into the UGVWs. We further discuss opportunities and challenges for mitigating harmful designs.

Online platforms like YouTube and Instagram have enabled the platformization and monetization of creative work, allowing content creators to derive revenue and thrive in a creator economy. While much work has been done to understand content creation on single platforms, the creative practice often involves content creators’ agency and practice to interact with multiple platforms and make strategic decisions to optimize such interactions. In this paper, we use an interview study with 21 cross-platform creators to understand how they negotiate with platforms in their creative practices through the construction of creator ecology. We found that participants developed priorities among platforms based on varied criteria, paid attention to cross-platform content synchronization, and stressed managing and converting audiences across platforms to grow their fanbase. Our findings highlight the complex interplay between creator agency and labor, as well as yield implications for future design possibilities of creator empowerment and support.

Automated machine learning (AutoML) is envisioned to make ML techniques accessible to ordinary users. Recent work has investigated the role of humans in enhancing AutoML functionality throughout a standard ML workflow. However, it is also critical to understand how users adopt existing AutoML solutions in complex, real-world settings from a holistic perspective. To fill this gap, this study conducted semi-structured interviews of AutoML users (N = 19) focusing on understanding (1) the limitations of AutoML encountered by users in their real-world practices, (2) the strategies users adopt to cope with such limitations, and (3) how the limitations and workarounds impact their use of AutoML. Our findings reveal that users actively exercise user agency to overcome three major challenges arising from customizability, transparency, and privacy. Furthermore, users make cautious decisions about whether and how to apply AutoML on a case-by-case basis. Finally, we derive design implications for developing future AutoML solutions.

Researchers across various fields have investigated how users experience moderation through different perspectives and methodologies. At present, there is a pressing need of synthesizing and extracting key insights from prior literature to formulate a systematic understanding of what constitutes a moderation experience and to explore how such understanding could further inform moderation-related research and practices. To answer this question, we conducted a systematic literature review (SLR) by analyzing 42 empirical studies related to moderation experiences and published between January 2016 and March 2022. We describe these studies' characteristics and how they characterize users' moderation experiences. We further identify five primary perspectives that prior researchers use to conceptualize moderation experiences. These findings suggest an expansive scope of research interests in understanding moderation experiences and considering moderated users as an important stakeholder group to reflect on current moderation design but also pertain to the dominance of the punitive, solutionist logic in moderation and ample implications for future moderation research, design, and practice.

Live streaming has become a popular activity world-wide that has warranted research attention on its privacy related issues. For instance, bystanders' privacy, or the privacy of third-parties captured by streamers, has been increasingly studied as live streaming has become almost ubiquitous in both public and private spaces in many countries. While prior work has studied bystanders' privacy concerns, a gap exists in understanding how streamers consider bystanders' privacy and the steps they take (or do not take) to preserve it. Understanding streamers' considerations towards bystanders' privacy is vital because streamers are the ones who have direct control over whether and how bystanders' information is disclosed. To address this gap, we conducted an interview study with 25 Chinese streamers to understand their considerations and practices regarding bystanders' privacy in live streaming. We found that streamers cared about bystanders' privacy and evaluated possible privacy violations to bystanders from several perspectives. To protect bystanders from privacy violations, streamers primarily relied on technical, behavioral, and collaborative strategies. Our results also indicated that current streaming platforms lacked features that helped streamers seamlessly manage bystanders' privacy and involved bystanders into their privacy decision-making. Applying the theoretical lens of collective privacy management, we discuss implications for the design of live streaming systems to support streamers in protecting bystanders' privacy.

The term “metaverse” was first introduced in Neal Stephenson’s 1992 science fiction novel, Snow Crash. It is conceived as the successor to the contemporary Internet, wherein users, represented as avatars, can interact with others or with applications within a three-dimensional (3D) virtual space, which is ubiquitously accessible. Although the metaverse remains a digital construct, establishing a sophisticated virtual societal framework—including a stable economic system—is paramount as users acquire assets and foster communities therein[4]. The implications become profound and potentially unpredictable should any single entity gain dominance over this virtual societal infrastructure. Such anxieties have been vividly portrayed in recent cinematic offerings such as “Ready Player One” and “Free Guy.” In response, blockchain technology emerges as a promising countermeasure. Trailblazing metaverse platforms leveraging blockchain, such as Decentraland, CryptoVoxels, and Sandbox, utilize cryptocurrency and nonfungible tokens (NFTs) to define programmable assets or access privileges[11]. These tokens may facilitate a borderless and frictionless payment layer, ensuring the uniqueness, persistence, and tradability of users’ digital assets[9]. Furthermore, the rise of smart contract-driven decentralized applications (DApps)[10]—spanning decentralized finance (DeFi) to innovative social applications[5]— ushers in an era of transparent, self-regulating digital ecosystems. As a multimedia community predicated upon vast online participation, advancements in blockchain may pave the way for a fair, transparent, and sustainable metaverse[13].

Chatbot-based symptom checker (CSC) apps have become increasingly popular in healthcare. These apps engage users in human-like conversations and offer possible medical diagnoses. The conversational design of these apps can significantly impact user perceptions and experiences, and may influence medical decisions users make and the medical care they receive. However, the effects of the conversational design of CSCs remain understudied, and there is a need to investigate and enhance users’ interactions with CSCs. In this article, we conducted a two-stage exploratory study using a human-centered design methodology. We first conducted a qualitative interview study to identify key user needs in engaging with CSCs. We then performed an experimental study to investigate potential CSC conversational design solutions based on the results from the interview study. We identified that emotional support, explanations of medical information, and efficiency were important factors for users in their interactions with CSCs. We also demonstrated that emotional support and explanations could affect user perceptions and experiences, and they are context-dependent. Based on these findings, we offer design implications for CSC conversations to improve the user experience and health-related decision-making.

Electronic health records (EHR) have been widely applied to various tasks in the medical domain such as risk predictive modeling, which aims to predict further health conditions by analyzing patients' historical EHR. Existing work mainly focuses on modeling the sequential and temporal characteristics of EHR data with advanced deep learning techniques. However, the network architectures of these models are all manually designed based on experts' prior knowledge, which largely impedes non-experts from exploring this task. To address this issue, in this paper, we propose a novel automated risk prediction model named AutoMed to automatically search the optimal model architecture for modeling the complex EHR data and improving the performance of the risk prediction task. In particular, we follow the idea of neural architecture search to design a search space that contains three separate searchable modules. Two of them are used for analyzing sequential and temporal features of EHR data, respectively. The third is to automatically fuse both features together. Besides these three modules, AutoMed contains an embedding module and a prediction module. All the three searchable modules are jointly optimized in the search stage to derive the optimal model architecture. In such a way, the model design can be automatically achieved with few human interventions. Experimental results on three real-world datasets show that AutoMed outperforms state-of-the-art baselines in terms of PR-AUC, F1, and Cohen's Kappa. Moreover, the ablation study shows that AutoMed can obtain reasonable model architectures and offer useful insights to the future risk prediction model design.

Patients with low health literacy usually have difficulty understanding medical jargon and the complex structure of professional medical language. Although some studies are proposed to automatically translate expert language into layperson-understandable language, only a few of them focus on both accuracy and readability aspects simultaneously in the clinical domain. Thus, simplification of the clinical language is still a challenging task, but unfortunately, it is not yet fully addressed in previous work. To benchmark this task, we construct a new dataset named MedLane to support the development and evaluation of automated clinical language simplification approaches. Besides, we propose a new model called DECLARE that follows the human annotation procedure and achieves state-of-the-art performance compared with eight strong baselines. To fairly evaluate the performance, we also propose three specific evaluation metrics. Experimental results demonstrate the utility of the annotated MedLane dataset and the effectiveness of the proposed model DECLARE.

Esports, like traditional sports, face governance challenges such as foul play and match fixing. The esports industry has seen various attempts at governance structure but is yet to form a consensus. In this study, we explore esports governance in League of Legends (LoL), a major esports title. Through a two-stage, mixed-methods analysis of rule enforcement that Riot Games, LoL's developer and publisher, has performed against esports participants such as professional players and teams, we qualitatively describe rule breaking behaviors and penalties in LoL esports, and quantitatively measure how contextual factors such as time, perpetrator identity, and region might influence governance outcomes. These findings about rule enforcement allow us to characterize the esports governance of LoL as top-down and paternalistic, and to reflect upon professional players' work and professionalization in the esports context. We conclude by discussing translatable implications for esports governance practice and research.

Live streaming is a popular synchronous social media platform that allows users to disclose information to vast audience in real time. It has been increasingly studied in recent years for its unique functions of disseminating user-generated content, enriching streamers' self-presentation, curating online social interactions and fostering online communities. However, little research has been done to explore the privacy issues in live streaming. In the present paper, we aim to understand streamers' privacy concerns and strategies in their information disclosure on live streaming. From an interview study with 20 streamers, we found that they expressed concerns and carefully managed their information disclosure based on whether the disclosure would enhance or weaken their attractiveness to the audience and whether it would disturb their interpersonal boundary with the audience. They adopted various technical and behavioral privacy management strategies to cope with their concerns, but encountered a series of usability and cognitive burdens. Based on the findings, we present design implications to improve the privacy management on live streaming.

In today’s fast-paced world, stress has become a growing health concern. While more automatic stress tracking technologies have recently become available on wearable or mobile devices, there is still a limited understanding of how they are actually used in everyday life. This paper presents an empirical study of automatic stress-tracking technologies in use in China, based on semi-structured interviews with 17 users. The study highlights three challenges of stress-tracking data engagement that prevent effective technology usage: the lack of immediate awareness, the lack of pre-required knowledge, and the lack of corresponding communal support. Drawing on the stress-tracking practices uncovered in the study, we bring these issues to the fore, and unpack assumptions embedded in related works on self-tracking and how data engagement is approached. We end by calling for a reconsideration of data engagement as part of self-tracking practices with technologies rather than simply looking at the user interface.

Online platforms rely upon users or automated tools to flag toxic behaviors, the very first step in online moderation. While much recent research has examined online moderation, the role of flag remains poorly understood. This question becomes even more urgent in automated moderation, where flagging becomes a primary source of human judgment. We conducted a qualitative study of flagging practices in League of Legends (LoL), a popular eSports game. We found stark differences between how flag is designed to identify toxicity, and flaggability, or how players use and appropriate flag. Players distrust flag, but also appropriate flag for instrumental purposes. Thus, flaggability diverges decidedly from the conception of toxicity, and must be understood within the highly competitive gaming context of LoL. These findings help shed light on the situated nature of flaggability, the role of flag in online moderation, as well as implications for designing flag and moderation.

Online symptom checkers (OSC) are widely used intelligent systems in health contexts such as primary care, remote healthcare, and epidemic control. OSCs use algorithms such as machine learning to facilitate self-diagnosis and triage based on symptoms input by healthcare consumers. However, intelligent systems’ lack of transparency and comprehensibility could lead to unintended consequences such as misleading users, especially in high-stakes areas such as healthcare. In this paper, we attempt to enhance diagnostic transparency by augmenting OSCs with explanations. We first conducted an interview study (N=25) to specify user needs for explanations from users of existing OSCs. Then, we designed a COVID-19 OSC that was enhanced with three types of explanations. Our lab-controlled user study (N=20) found that explanations can significantly improve user experience in multiple aspects. We discuss how explanations are interwoven into conversation flow and present implications for future OSC designs.

Recently, consumer-facing health technologies such as Artificial Intelligence (AI)-based symptom checkers (AISCs) have sprung up in everyday healthcare practice. AISCs solicit symptom information from users and provide medical suggestions and possible diagnoses, a responsibility that people usually entrust with real-person authorities such as physicians and expert patients. Thus, the advent of AISCs begs a question of whether and how they transform the notion of medical authority in people's everyday healthcare practice. To answer this question, we conducted an interview study with thirty AISC users. We found that users assess the medical authority of AISCs using various factors including AISCs’ automated decisions and interaction design patterns, associations with established medical authorities like hospitals, and comparisons with other health technologies. We reveal how AISCs are used in healthcare delivery, discuss how AI transforms conventional understandings of medical authority, and derive implications for designing AI-enabled health technology.

People with multiple chronic conditions (MCC) often face complex and overwhelming conflicts in their personal health management. However, little is known about how technology can help users to address these challenges. Better understanding the practices involved in conflict resolution is necessary to guide the design of technology aiming to support this population. This interview study investigated the strategies seniors use to overcome conflicts involving different health issues, their self-care tasks, risks of another illness or complication, and their personal values. We report on the different strategies used to address these conflicts, such as seeking advice and information from different sources to prioritize and compromise. Compromising often involves purposefully deciding against conventional treatments or self-care activities. We argue that rich information and flexibility are required to support decision making in MCC self-care, and advocate for a holistic perspective in technology design for health management. These implications also apply to systems focused on a single illness, as many of their users might live with other conditions.

2020's COVID-19 crisis has given rise to ubiquitous emergency remote learning (ERL). Guardians, mostly parents, have had to help their children transition and adapt to this difficult learning context. Previous work on remote learning has explored guardian involvement in pre-planned and well-developed remote learning programs, such as established virtual schools. However, ERL lacks pre-planned procedures, policies, and resources. In this paper, we look at how teachers and guardians collaborated to manage the situation. We present an interview study of guardians and teachers of K-12 students in China and look at their collaboration during the COVID-19 ERL. We report how teachers and guardians collaborated to carry out techno-procedural, surveillance, and material work to make ERL possible for K-12 students. Lastly, we reflect on the challenges our participants faced and discuss design implications not only for remote learning during COVID-19 but also future emergency remote learning situations.

Crisis informatics research has examined geographically bounded crises, such as natural or man-made disasters, identifying the critical role of local and hyper-local information focused on one geographic area in crisis communication. The COVID-19 pandemic represents an understudied kind of crisis that simultaneously hits locales across the globe, engendering an emergent form of crisis communication, which we term cross-local communication. Cross-local communication is the exchange of crisis information between geographically dispersed locales to facilitate local crisis response. To unpack this notion, we present a qualitative study of an online migrant community of overseas Taiwanese who supported fellow Taiwanese from afar. We detail four distinctive types of cross-local communication: situational updates, risk communication, medical consultation, and coordination. We discuss how the current pandemic situation brings new understandings to crisis informatics and online health community literature, and what role digital technologies could play in supporting cross-local communication.

Online Ask the Doctor (AtD) services allow access to health professionals anytime anywhere beyond existing patient-provider relationships. Recently, many free-market AtD platforms have emerged and been adopted by a large scale of users. However, it is still unclear how people make use of these AtD platforms in practice. In this paper, we present an interview study with 12 patients/caregivers who had experience using AtD in China, highlighting patient agency in seeking more reliable and cost-effective healthcare beyond clinic settings. Specifically, we illustrate how they make strategic choices online on AtD platforms, and how they strategically integrate online and offline services together for healthcare. This paper contributes an empirical study of the use of large-scale AtD platforms in practice, demonstrates patient agency for healthcare beyond clinic settings, and recommends design implications for online healthcare services.

Millions of surgeries are performed in the US annually, and numbers are trending upwards. Traditional rehabilitative interventions are struggling to meet current demands, and researchers have turned to pre-operative interventions, or prehabilitation, to improve patient functions. However, existing literature primarily discusses efficacy or the use of commercial sensing devices, and lacks a clear comprehension of healthcare professionals' (HPs') needs and perspectives. User-centered stakeholder understandings are crucial for a technology's adoption, but prehabilitation literature lacks such understandings. Therefore we conduct semi-structured interviews with 12 prehabilitation healthcare professionals (HPs) to offer descriptions of care challenges, tool usage, and perspectives regarding suitable and effective technologies. These data can assist designers in fostering prehabilitation processes via tailored prehabilitation tools which meet HPs' needs and expectations.

Artificial intelligence (AI) has become prevalent in our everyday technologies and impacts both individuals and communities. The explainable AI (XAI) scholarship has explored the philosophical nature of explanation and technical explanations, which are usually driven by experts in lab settings and can be challenging for laypersons to understand. In addition, existing XAI research tends to focus on the individual level. Little is known about how people understand and explain AI-led decisions in the community context. Drawing from XAI and activity theory, a foundational HCI theory, we theorize how explanation is situated in a community's shared values, norms, knowledge, and practices, and how situated explanation mediates community-AI interaction. We then present a case study of AI-led moderation, where community members collectively develop explanations of AI-led decisions, most of which are automated punishments. Lastly, we discuss the implications of this framework at the intersection of CSCW, HCI, and XAI.

Today eSports gaming is enjoying growing popularity in the world and much attention from various research areas, including CSCW. eSports gaming is a highly competitive environment commonly associated with negative emotions such as anxiety and stress. However, little attention has been paid to emotion regulation in eSports gaming. In this study, we empirically investigated how players experience emotion and regulate emotions in League of Legends, one of the largest eSports games today. We identify four emotive factors, as well as emotion regulation strategies that players deploy to manage the emotions of their selves, teammates, and opponents. We further report on how they use emotion regulation in emotional self-care and emotional leadership. Building upon this set of findings, we discuss how the competitive eSports gaming context conditions emotion regulation in League of Legends, foreground emotion regulation expertise in competitive gaming, and derive implications for designing emotion regulation technologies.

Many mobile games are designed to be placeless, so that mobile device owners could play anytime, anywhere. But does such design erase the sense of place in mobile gaming? To investigate the spatiality of mobile gaming, we conducted an ethnographic study of mobile gaming in a Chinese university. We found mobile gaming as a form of collocated interaction, where participants collectively created meanings around distinctive places on the campus including dormitory, classroom, and laboratory, and engaged in collaborative play. Their mobile collocated gaming was shaped by the social, organizational, and cultural contexts of places. The spatiality of mobile collocated gaming entails both appropriation of the norms and expectations of places and creation of new meanings to negotiate tensions between mobile gaming and places. We further discuss the spatiality of mobile collocated gaming and broader social and cultural conditions.

The U.S. healthcare infrastructure is fragmented with various breakdowns. Patients or caregivers have to rely on their own to overcome barriers and fix breakdowns in order to obtain necessary service, that is, infrastructuring work to make the healthcare infrastructure work for them. So far little attention has been paid to such infrastructuring work in healthcare. We present an interview study of 32 U.S. parents of young children to discuss the work of infrastructuring our participants carry out to deal with breakdowns within the healthcare infrastructure. We report how they repaired unexpected failures happening at the individual level, aligned components at organizational and cross-organizational level, and circumvented infrastructural constraints (e.g., policy and financial ones) that were perceived as ambiguous and demanding. We discuss infrastructuring work in light of the literature on patients' and caregivers' work, reflect upon the notion of patient engagement, and explore nuances along several dimensions of infrastructuring work.

Everyday life is increasingly mediated by technology. Technology is rapidly growing capacity and complexity, especially evident in developments in artificial intelligence and big data analytics. As human-computer interaction (HCI) endeavors to examine and theorize how people act and interact with the ever-evolving technology, an important, emerging concern is how the self-the totality of internal qualities such as consciousness and agency-plays out in relation to the technology-mediated external world. To analyze this question, we draw from Michel Foucault's ethics of "care of the self," which examines how the self is constituted through conscious and reflective work on self-transformation. We present three case studies to illustrate how individuals carry out practices of the self to reflect upon and negotiate their relationship with technology. We discuss the importance of examining the self and foreground the notion of care of the self in HCI research and design.

Live streaming is a highly participatory form of performance, involving various types of audience participation such as liking, commenting, and gifting. But how do streamers and audiences collaborate to deliver live streaming performances? We approach this question through an interview study with 30 spectators and eight streamers in China. Drawing from theatrical engagement research, we use the cogitative spatial concept of center-peripheral attention of the audience to analyze the complex interplay between streamers and spectators, where the former occupy the center and the latter the periphery. We then discuss the orchestration of the center and the periphery, where streamers and spectators coordinate their respective performances, as well as the interaction between the center and the periphery, where the center-periphery distinction blurs. Based on these findings, we discuss co-performance as a theatrical metaphor for understanding live streaming and audience engagement.

Social media is often analyzed as a "front stage" where social media users perform their identities and manage impressions through various forms of user-generated content: text, picture, video, as well as visual expression such as emoticon, emoji, sticker, and meme. Previous scholarship has suggested various functions of visual expression in supporting computer-mediated communication. In this study, we move beyond the utility perspective to ask what constitutes the literacy to utilize visual expression for impression management. Towards this goal, we conducted an interview study with 30 social media users in China. We found that visual literacy intersects with its cultural context. Our interviewees used text and visual expressions in sophisticated, skillful ways and tailored for different audiences in order to construct desired images. They also interacted with audience memory in order to perform their uniqueness and creativity. Lastly, we discuss culturally-embedded visual literacy and provide implications for design.

Crisis informatics has examined how institutions and individuals seek, communicate, and curate information in response to crises. The public's communication and perception of risks on social media remain understudied. In this study, we report a qualitative analysis of public perceptions of risks and risk management measures on Reddit during the Zika crisis, an emerging epidemic associated with high uncertainty regarding pathology, epidemiology, and broad consequences. We found two types of perceived risks: ones directly caused by the Zika virus, and ones potentially introduced by authorities' risk management measures. Risk perceptions unfolded along multiple dimensions beyond the imminent and personal level. Reddit users discussed in a speculative way to foresee various risks in the long run or at larger geographical scales. We discuss the multidimensionality and speculative nature of risk perception on social media, and derive implications for crisis informatics research and public health research and practice.

Streakiness refers to observed tendency towards consecutive appearances of particular patterns. In video games, streakiness is oftentimes inevitable, where a player keeps winning or losing for a short period. However, the phenomenon remains understudied in present online game research. How do players perceive streakiness? How does it impact player experience (PX)? How should streakiness be taken into consideration for the design of PX? In this paper, we address these questions through a qualitative study of player discussions about streakiness in League of Legends. We found that players developed various ways to describe a streak. Both winning and losing streaks negatively impacted PX. Players devised numerous strategies to manage streakiness, among which disengagement was a primary means. We analyze streakiness as a social construct through which players coped with complex game systems. We discuss design implications for managing streakiness in online games.

CSCW research has investigated how people at workplace and organizational settings gain knowledge required for work, but less is known regarding how "organizational outsiders" obtain knowledge about organizations and organizational landscapes that provide a service. Gaining knowledge about service landscapes is particularly difficult because they are often complex, non-transparent, and fragmented. We address this gap through an interview study of 19 U.S. parents regarding how they navigated health services for their young children, and how they gained competence in navigation practices. We describe a similar process all participants went through including four inherently iterative stages: seeking and integrating knowledge, decision-making, encountering breakdowns, and repairing and reflecting. We further elucidate what constitutes navigational competence, or the creation of resources about how to navigate, for our participants. We discuss how our study could advance understanding of navigation practices, and the importance for HCI design to support these complex yet essential navigation practices and the accumulation of navigational competence.

Quantification is a process that produces and communicates numbers, imbued with the expectation of generating knowledge and optimizing human behavior and social process. In this paper, we explore how quantification mediates virtual teamwork through an ethnographic study of quantification in League of Legends, a popular team-based online game with a highly competitive culture. In the game, rich statistics about each individual player's gaming history and performance are publicly available, analyzed and displayed on numerous third-party sites. We describe how players were entangled with numbers. They derived knowledge from numbers but struggled with proper ways of interpretation. They utilized numbers to quantify teammates and opponents, but in-game tensions and conflicts easily ensued. They noticed how quantification became burdensome and stressed the importance of proper use. We discuss how this case of quantified self and others manifests complex relationships between self-knowledge, numerical authority, and virtual teamwork.

Privacy researchers have suggested various granular audience control techniques for users to manage the access to their disclosed information on social network sites. However, it is unclear how users adopt and utilize such techniques in daily use and how these techniques may impact social interactions with others over time. In this study, we examine users' experience during everyday use of granular audience control techniques in WeChat, one of the most popular social network applications in China. Through an interview study with 24 WeChat users, we find that users adjust their configurations and develop rationales for these configurations over time. They also perceive mixed impacts of WeChat's privacy settings on their information disclosure and social interactions, which brings new challenges to privacy design. We discuss the implications of these findings and make suggestions for the future design of privacy settings in SNSs.

Timely access to professional medical advice is crucial for patient health outcomes. Traditional offline, one-on-one patient-provider interactions are time consuming and costly. As a result, online "Ask the doctor" (AtD) services have become increasingly popular, where patients and caregivers can obtain advice from medical professionals at a lower information and transaction cost. In this paper, we present an empirical study of Fenda, an innovative AtD platform recently introduced in China where patients and caregivers can consult a wide variety of healthcare professionals for a small fee. Using qualitative research methods, we analyzed how patients and caregivers interact with medical professionals on this platform, focusing on the nature of the questions asked and user strategies to optimize the usage of the platform. We further derived implications for designing better online AtD services connecting patients and caregivers to medical professionals.

The last two decades have seen growing interest in promoting physical activities by using self-tracking technologies. Previous work has identified social interactions in self-tracking as a crucial factor in motivating users to exercise. However, it is unclear how integrating fitness features into complex pre-existing social network affects users' fitness tracking practices and social interactions. In this research, we address this gap through a qualitative study of 32 users of WeRun--a fitness plugin of the widely adopted Chinese mobile social networking service WeChat. Our findings indicate that sharing fitness data with pre-existing social networks motivates users to continue self-tracking and enhances their existing social relationships. Nevertheless, users' concerns about their online personal images lead to challenges around privacy. We discuss how our study could advance understanding of the effects of fitness applications built on top of pre-existing social networks. We present implications for future social fitness applications design.

Recently, diseases like H1N1 influenza, Ebola, and Zika virus have created severe crises, requiring public resources and personal behavior adaptation. Crisis Informatics literature examines interconnections of people, organizations, and IT during crisis events. However, how people use technology to cope with disease crises (outbreaks, epidemics, and pandemics) remains understudied. We investigate how individuals used social media in response to the outbreak of Zika, focusing on travel-related decisions. We found that extreme uncertainty and ambiguity characterized the Zika virus crisis. To cope, people turned to social media for information gathering and social learning geared towards personal risk assessment and modifying decisions when dealing with partial and conflicting information about Zika. In particular, individuals sought local information and used socially informed logical reasoning to deduce the risk at a specific locale. We conclude with implications for designing information systems to support individual risk assessment and decision-making when faced with uncertainty and ambiguity during public health crises.

We report a study of peer support in online health communities for pregnancy care along three gestational stages (trimesters) to investigate how pregnant women seek and receive peer support during different stages of pregnancy. Using Babycenter.com as our research setting, we found that pregnant women sought peer support due to constrained access to healthcare providers, dissatisfaction with healthcare services/medical advice, limited offline social support, and unavailability of information in other venues. While the particular topics of concern typifying each trimester were distinct, pregnant women consistently sought advice, informal and formal knowledge, reassurance, and emotional support from peers during each stage of pregnancy. BabyCenter.com peers provided support by leveraging their own experiential knowledge and passing along clinical expertise acquired during the course of their own healthcare. We discuss design implications for health services and IT systems that meet pregnant women's temporal and multi-faceted needs during prenatal care.

Conspiracy theories have gained much academic and media attention recently, due to their large impact on public events. Crisis informatics researchers have examined conspiracy theories as a type of rumor. However, little is known about how conspiracy theories are produced and developed on social media. We present a qualitative study of conspiracy theorizing on Reddit during a public health crisis--the Zika virus outbreak. Using a mixed-methods approach including content analysis and discourse analysis, we identified types of conspiracy theories that appeared on Reddit in response to the Zika crisis, the conditions under which Zika conspiracy theories emerge, and the particular discursive strategies through which Zika conspiracy theories developed in online forums. Our analysis shows that conspiracy talk emerged as people attempted to make sense of a public health crisis, reflecting their emergent information needs and their pervasive distrust in formal sources of Zika information. Practical implications for social computing researchers, health practitioners, and policymakers are discussed.

Disruptive behaviors such as flaming and vandalism have been part of the Internet since its beginning. Various models of hierarchical governance have been established and managed in different online venues, with both successes and failures. Recently, a new model of non-hierarchical governance has emerged using crowdsourcing technology to allow an online community to manage itself. How do people view and work with non-hierarchical governance? In this paper, we present an interview study with people from two sites: the video game League of Legends and Weibo, a microblogging site in China. We found that people were passionate about participation in crowdsourcing, but at the same time, struggled with the system, and acted beyond their designated role within the system. We derive implications for designing online non-hierarchical governance from our research.