Content Moderation with Shadowbanning

Social media platforms face increasing pressure to moderate harmful content while preserving user engagement and free expression. We examine shadowbanning—a strategy that hides content without notifying the user—and compare it to traditional content removal. Our results show that if users only moderately believe that shadowbanning occurs, the platform benefits from a larger user base and higher profit, which also leads to greater social welfare than with content removal or no moderation. Shadowbanning allows the platform to reduce users’ exposure to extreme content without deterring content creators, enabling more participation of users across the extremeness spectrum. However, outcomes depend on user beliefs and the accuracy of moderation technology. When users are highly suspicious of shadowbanning or when moderation tools are significantly imperfect, the platform’s incentives—and the societal benefits—decline. These findings offer practical insights for platform designers and regulators: shadowbanning can be effective, but its benefits hinge on how transparently and accurately it is implemented. Policymakers should account for user perceptions and technological capabilities when evaluating or regulating opaque moderation strategies.

• 저널Information Systems Research
• 토픽Hate Speech and Cyberbullying Detection · Artificial Intelligence
• DOI10.1287/isre.2024.1140
• 저자Afrouz Hojati, Barrie R. Nault