Community Fact-Checks Do Not Break Follower Loyalty

2025-05-15

AI Summary

Prior research on community fact-checking has predominantly examined user engagement metrics, neglecting the critical dimension of follower loyalty—particularly whether fact-checking deters misinformation producers by eroding their audience base. Method: Leveraging longitudinal follower data from 3,516 fact-checked posts on X (formerly Twitter), we employ a quasi-experimental design combined with event-study analysis to causally identify the impact of fact-checking on follower counts. Contribution/Results: We find no statistically significant decline in followers following fact-checking, challenging the implicit “fact-checking-as-punishment” assumption. Followers exhibit substantial tolerance, and creator loyalty remains largely unaffected. This study provides the first empirical evidence that community fact-checking exerts limited efficacy in retaining—or deterring—misinformation producers at the user-level retention margin. Consequently, relying solely on fact-checking is insufficient for curbing misinformation supply; complementary governance mechanisms—such as platform incentives, algorithmic demotion, or content moderation—are necessary.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Application Domains: Misinformation & Fake News
• Data Mining & Knowledge Management: Graph Mining, Social Network Analysis & Community

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• Responsible Web: Mitigating misinformation and disinformation
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

Major social media platforms increasingly adopt community-based fact-checking to address misinformation on their platforms. While previous research has largely focused on its effect on engagement (e.g., reposts, likes), an understanding of how fact-checking affects a user's follower base is missing. In this study, we employ quasi-experimental methods to causally assess whether users lose followers after their posts are corrected via community fact-checks. Based on time-series data on follower counts for N=3516 community fact-checked posts from X, we find that community fact-checks do not lead to meaningful declines in the follower counts of users who post misleading content. This suggests that followers of spreaders of misleading posts tend to remain loyal and do not view community fact-checks as a sufficient reason to disengage. Our findings underscore the need for complementary interventions to more effectively disincentivize the production of misinformation on social media.

Problem

• Assessing impact of community fact-checks on follower loyalty
• Evaluating if misleading posts lead to follower loss
• Exploring need for additional interventions against misinformation

Innovation

• Quasi-experimental methods assess follower loyalty
• Time-series data analysis on 3516 fact-checked posts
• Community fact-checks do not reduce follower counts