Balancing Acts: Unveiling the Dynamics of Post Removal on Social Media User-Generated Content

Policy and Practice Abstract User-generated content (UGC) is central to engagement and value creation on social media platforms, but policy violations and low-quality posts create significant reputational, legal, and financial risks. Platforms commonly respond by removing posts that violate community standards, yet it remains unclear whether such actions deter users from contributing or instead improve subsequent behavior. Analyzing data from 40 Reddit communities using a difference-in-differences design, we examine how post removal influences users’ future contributions. We find that removing a user’s post reduces subsequent rule violations and increases the average number of upvotes their later posts receive, an indicator of improved content quality. These effects are stronger when users experience repeated removals and when they observe peers’ posts being removed, highlighting both direct and vicarious learning mechanisms. For platform operators, the findings suggest that targeted, consistent, and transparent post removal can serve as an effective governance tool, not merely to suppress harmful content but to foster higher-quality participation over time. For policymakers and regulators, the results underscore the importance of moderation frameworks that promote user learning, accountability, and procedural fairness. Well-designed moderation systems can enhance community standards while maintaining legitimacy and trust in digital governance.

• 저널Information Systems Research
• 토픽Hate Speech and Cyberbullying Detection · Artificial Intelligence
• DOI10.1287/isre.2023.0750
• 저자Guohou Shan, Liangfei Qiu