Social computing researchers increasingly use TikTok data to understand social media's impact on society. As legal mandates requiring social media platforms to share data with researchers go into effect, platforms, regulators, and researchers are all being asked to consider platform users' expectations about ethical uses of their data. The framework of contextual integrity has come to dominate research into users' concerns about research uses of their social media data. How well does contextual integrity account for users' expectations when users may be unaware of research uses of social media data? This qualitative, exploratory study used interviews centered around a card sorting activity to help TikTok users reflect upon their understanding of data flows, their perceptions of researchers' data use, and their expectations of TikTok research. The findings suggest something interesting for both privacy researchers and social computing researchers: young adults were surprised by research uses of TikTok data (traditionally understood as a violation of contextual integrity), but confidently referenced existing privacy-preserving practices and knowledge of data harms to assess the acceptability of researcher data use. Participants performed what we label context import, relying on their grasp of digital surveillance to reason through the social media researcher context. Researchers advising policymakers and platforms on the privacy expectations of users should be aware of the ways in which context import might impact user's perspectives of lesser understood contexts. Findings relevant to social computing researchers include that context import informed participants' awareness of data uses, and also enabled participants to express concerns specifically relevant to research uses of TikTok data, including the importance of cultural and political contexts, treatment of previously public content, pressures to share, and expanding concerns regarding biometric data.

Online content moderation has become the subject of intense debate as policymakers and platform developers aim to balance values such as freedom of expression and community safety. Despite the impact of content moderation on public discourse and online experiences, the debate surrounding content moderation regulation rarely involves those impacted by these decisions. To explore how to engage individuals in learning opportunities that deepen understanding of social and technical aspects of online content moderation, we designed and tested an educational game: CONTENTR. The game gives participants experience debating and making decisions about platform governance. We used the Values at Play (VAP) game design framework to discover and translate social values into game elements, and then verified both values translation and learning outcomes using qualitative feedback from three phases of testing. We found that gameplay facilitated collaborative discussion and decision-making regarding the challenges of designing an online platform for mass appeal. Both tabletop and online versions of the game are available on our project website. Our findings highlight how gameplay can create a deeper understanding of the challenges involved in developing and enforcing online content policies, and challenge participants' pre-existing values and assumptions through both game elements and exposure to other participants' perspectives. We believe the game will be useful in courses ranging from civics and technology policy to information and computer science.

Fueled by Internet-of-Things technologies and spanning a wide range of sensors, speakers, and cameras, smart homes promise to make our lives easier and automate routine tasks. From speakers to security cameras, smart home devices (SHDs) answer our questions, monitor our home environment, and conserve energy. They also collect significant data, ranging from on/off commands to audio and video data, and they do this in some of our most private spaces. In this paper, we explore the privacy risks associated with SHDs by focusing on privacy-conscious smart home power users--those who spend significant time and money to research, install, and integrate devices throughout their homes and engage in advanced device and network management strategies to mitigate privacy concerns. Drawing on data from 10 focus groups with 32 privacy-conscious power users, we identify the key privacy risks they perceive from this technology, as well as how they mitigate those risks through increasingly complex strategies. Our findings reveal that navigating the technical landscape that makes up the smart home environment--including what data is collected, what options are available for managing or restricting data flows, and who has access to data collected by SHDs--is complex and often confusing, even for people who spend significant time researching devices and integration options. We use these findings to argue for further development of tools that are transparent, easy to use, and aligned with the privacy needs of a diverse userbase.