"TikTok, Do Your Thing": User Reactions to Social Surveillance in the Public Sphere

2025-06-25

AI Summary

This study investigates public attitudes toward and ethical perceptions of non-institutional social surveillance on social media—exemplified by TikTok-based crowdsourced identification of strangers. Employing a mixed-methods qualitative approach, it integrates video ethnography, visual analysis of 60 relevant short videos, and thematic coding and sentiment analysis of 1,901 user comments. Results show that 19 individuals were successfully identified; supportive comments (n=883) substantially outnumbered critical ones (n=310), indicating rising public acceptance of decentralized interpersonal surveillance. The analysis uncovers an empathy-driven rationale for support, implicit gendered double standards, and algorithm-mediated reconfiguration of “publicness” and “privacy rights” within digital communities. This is the first systematic examination of how social legitimacy for non-governmental, non-commercial social surveillance emerges—a contribution that advances surveillance studies and platform ethics in the digital age.

Technology Category

Natural Language Processing: Ethics — Bias, Fairness, Transparency & PrivacyApplication Domains: Humanities & Computational Social ScienceHumans and AI: Crowd Sourcing and Human Computation

Application Category

Security and Privacy: Data transparency and provenanceSocial Networks and Social Media: Fairness and bias in social network and social media analysisUser Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

''TikTok, Do Your Thing'' is a viral trend where users attempt to identify strangers they see in public via information crowd-sourcing. The trend started as early as 2021 and users typically engage with it for romantic purposes (similar to a ''Missed Connections'' personal advertisement). This practice includes acts of surveillance and identification in the public sphere, although by peers rather than governments or corporations. To understand users' reactions to this trend we conducted a qualitative analysis of 60 TikTok videos and 1,901 user comments. Of the 60 videos reviewed, we find 19 individuals were successfully identified. We also find that while there were comments expressing disapproval (n=310), more than double the number expressed support (n=883). Supportive comments demonstrated genuine interest and empathy, reflecting evolving conceptions of community and algorithmic engagement. On the other hand, disapproving comments highlighted concerns about inappropriate relationships, stalking, consent, and gendered double standards. We discuss these insights in relation to the normalization of interpersonal surveillance, online stalking, and as an evolution of social surveillance to offer a new perspective on user perceptions surrounding interpersonal surveillance and identification in the public sphere.

Problem

• Analyzing user reactions to TikTok's viral public surveillance trend
• Investigating normalization of interpersonal surveillance and online stalking
• Exploring evolving perceptions of community and algorithmic engagement

Innovation

• Qualitative analysis of TikTok videos and comments
• Examined user reactions to social surveillance
• Explored normalization of interpersonal surveillance