Automated Comment Moderation Enhances Social Media Advertising Performance

RESUMO

Social media advertising exposes brands not only to potential customers but also to unfiltered consumer discourse in the form of user comments. While comments can enhance authenticity and engagement, they also introduce reputational risks through spam, hate speech, and negative user-generated content. Despite the increasing prevalence of AI-powered comment moderation solutions, little causal evidence exists on whether moderation (i.e., hiding harmful comments) improves ad effectiveness. Across six empirical studies-including two large-scale field experiments and four online studies-we demonstrate that automated moderation of harmful comments causally improves ad performance, including conversion rates, return on ad spend, and purchase intentions. We also identify two important platform-governance boundary conditions: the gains from moderation depend on whether the platform is transparent about the brand's moderation behavior, and what types of comments are moderated. At the same time, the moderation effect persists when the brand is transparent about its own moderation practices. We advance theory on context effects in social media advertising, by uncovering the first targeted, preventative intervention for avoiding negative adjacencies. For managers, the results show that AI-assisted comment moderation impacts real ad performance but may be contingent upon platform-level transparency design.