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Collaboratively adding context to social media posts reduces the sharing of false news
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We build a novel database of around 285,000 notes from the Twitter Community Notes program to analyze the causal influence of appending contextual information to potentially misleading posts on their dissemination. Employing a difference in difference design, our findings reveal that adding context below a tweet reduces the number of retweets by almost half. A significant, albeit smaller, effect is observed when focusing on the number of replies or quotes. Community Notes also increase by 80% the probability that a tweet is deleted by its creator. The post-treatment impact is substantial, but the overall effect on tweet virality is contingent upon the timing of the contextual information's publication. Our research concludes that, although crowdsourced fact-checking is effective, its current speed may not be adequate to substantially reduce the dissemination of misleading information on social media.
Forward citations
Cited by 2 Pith papers
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Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation
CrowdNotes+ combines LLM note augmentation and automation with a three-stage evaluation to outperform human contributors on correctness, helpfulness, and evidence utility for health misinformation notes.
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Community Moderation and the New Epistemology of Fact Checking on Social Media
Community-driven fact-checking is promising and useful, but it cannot fully replace professional fact-checkers; hybrid collaboration is the recommended path.
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