I Feel Like All of This Is Already Happening Anyways?: Context Import and Young Adults' Perspectives on Researcher Access to TikTok Data
Anna Lenhart, Katie Shilton
Abstract
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.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Cited by top-tier papers1
Ask how each one uses itRelated papers
- A Roadmap for Applying the Contextual Integrity Framework in Qualitative Privacy ResearchPriya C. Kumar, Michael Zimmer, Jessica VitakCSCW 2024 · 22 citations
- "Impressively Scary: ' Exploring User Perceptions and Reactions to Unraveling Machine Learning Models in Social Media ApplicationsJack West, Bengisu Cagiltay, Shirley Zhang, Jingjie Li et al.CHI 2025 · 2 citations
- The Algorithmic Crystal: Conceptualizing the Self through Algorithmic Personalization on TikTokAngela Y. Lee, Hannah Mieczkowski, Nicole B. Ellison, Jeffrey T. HancockCSCW 2022 · 127 citations
- "I See Me Here": Mental Health Content, Community, and Algorithmic Curation on TikTokAshlee Milton, Leah Ajmani, Michael Ann DeVito, Stevie ChancellorCHI 2023 · 115 citations
- Short-Form Videos Degrade Our Capacity to Retain Intentions: Effect of Context Switching On Prospective MemoryFrancesco Chiossi, Luke Haliburton, Changkun Ou, Andreas Martin Butz et al.CHI 2023 · 79 citations
