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.

翻译：在线社区并非用户隐私的安全空间。尽管现有研究侧重于创建和改进各类内容审核策略及隐私保护技术，但托管在线社区的平台仍支持用户相互监控的功能——这导致骚扰、个人数据泄露及线下伤害事件频发。为解决该问题，我们提出一种尚处于研究阶段的新框架，用于分析脆弱性身份型在线社区的数据隐私问题。当前SOUPS研究将监控与纵向用户数据视为用户隐私面临的两大独立挑战，而监控与历史用户数据交汇场景的探索仍需加强。通过综合四十余年来监控分析领域的发展成果，我们归纳出使社区成员能够滥用用户数据的在线社区特性，并提出改善脆弱用户安全的关键步骤。将这一新框架应用于新兴及现有平台，将确保在线社区具备隐私意识并以更具包容性的方式设计。