Peer Surveillance in Online Communities

TL;DR

This paper introduces a new framework for analyzing data privacy in vulnerable online communities, focusing on surveillance and user data abuse to improve security and inclusivity.

Contribution

It synthesizes 40 years of surveillance analysis to identify properties enabling data abuse and proposes steps to enhance privacy in online communities.

Findings

Identifies properties enabling user data abuse in online communities

Synthesizes historical surveillance analysis for privacy insights

Suggests key steps for more inclusive, privacy-conscious platform design

Abstract

Online communities are not safe spaces for user privacy. Even though existing research focuses on creating and improving various content moderation strategies and privacy preserving technologies, platforms hosting online communities support features allowing users to surveil one another--leading to harassment, personal data breaches, and offline harm. To tackle this problem, we introduce a new, work-in-progress framework for analyzing data privacy within vulnerable, identity-based online communities. Where current SOUPS papers study surveillance and longitudinal user data as two distinct challenges to user privacy, more work needs to be done in exploring the sites where surveillance and historical user data assemble. By synthesizing over 40 years of developments in the analysis of surveillance, we derive properties of online communities that enable the abuse of user data by fellow community members and suggest key steps to improving security for vulnerable users. Deploying this new framework on new and existing platforms will ensure that online communities are privacy-conscious and designed more inclusively.