# Community-based fact-checking reduces the spread of misleading posts on social media

arXiv: https://arxiv.org/abs/2409.08781 · HTML: https://mlsanity.com/paper/2409.08781/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Sep 2024.

## Built on by (most cited first, 7 of 7)

- [Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation](https://mlsanity.com/paper/2510.11423/) (2025)
- [COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations](https://mlsanity.com/paper/2510.24810/) (2025)
- [Multi-Agent Retrieval-Augmented Framework for Evidence-Based Counterspeech Against Health Misinformation](https://mlsanity.com/paper/2507.07307/) (2025)
- [Truth with a Twist: The Rhetoric of Persuasion in Professional vs. Community-Authored Fact-Checks](https://mlsanity.com/paper/2601.14105/) (2026)
- [Better with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notes](https://mlsanity.com/paper/2606.02215/) (2026)
- [Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking](https://mlsanity.com/paper/2607.01824/) (2026)
- [Community-Driven API and AI Writer Design for Openly Scaling Community Notes](https://mlsanity.com/paper/2609.40067/) (2026)

## Abstract (arXiv)

Community-based fact-checking is a promising approach to verify social media content and correct misleading posts at scale. Yet, causal evidence regarding its effectiveness in reducing the spread of misinformation on social media is missing. Here, we performed a large-scale empirical study to analyze whether community notes reduce the spread of misleading posts on X. Using a Difference-in-Differences design and repost time series data for N=237,677 (community fact-checked) cascades that had been reposted more than 431 million times, we found that exposing users to community notes reduced the spread of misleading posts by, on average, 62.0%. Furthermore, community notes increased the odds that users delete their misleading posts by 103.4%. However, our findings also suggest that community notes might be too slow to intervene in the early (and most viral) stage of the diffusion. Our work offers important implications to enhance the effectiveness of community-based fact-checking approaches on social media.