Did the Roll-Out of Community Notes Reduce Engagement With Misinformation on X/Twitter?
Not on the map. Why?
Abstract (arXiv)
Developing interventions that successfully reduce engagement with misinformation on social media is challenging. One intervention that has recently gained great attention is X/Twitter's Community Notes (previously known as "Birdwatch"). Community Notes is a crowdsourced fact-checking approach that allows users to write textual notes to inform others about potentially misleading posts on X/Twitter. Yet, empirical evidence regarding its effectiveness in reducing engagement with misinformation on social media is missing. In this paper, we perform a large-scale empirical study to analyze whether the introduction of the Community Notes feature and its roll-out to users in the U.S. and around the world have reduced engagement with misinformation on X/Twitter in terms of retweet volume and likes. We employ Difference-in-Differences (DiD) models and Regression Discontinuity Design (RDD) to analyze a comprehensive dataset consisting of all fact-checking notes and corresponding source tweets since the launch of Community Notes in early 2021. Although we observe a significant increase in the volume of fact-checks carried out via Community Notes, particularly for tweets from verified users with many followers, we find no evidence that the introduction of Community Notes significantly reduced engagement with misleading tweets on X/Twitter. Rather, our findings suggest that Community Notes might be too slow to effectively reduce engagement with misinformation in the early (and most viral) stage of diffusion. Our work emphasizes the importance of evaluating fact-checking interventions in the field and offers important implications to enhance crowdsourced fact-checking strategies on social media.
Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Jul 2023.
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Citing papers per year: 2025: 2; 2026: 9.
11 papers.
- 2025Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformationcited by 10
- 2025Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformationcited by 3
- 2026Causally Disentangled Contrastive Learning for Multilingual Speaker Embeddingscited by 2
- 2026GitSearch: Enhancing Community Notes Generation with Gap-Informed Targeted Searchcited by 2
- 2026The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformationcited by 1
- 2026What do people want to fact-check?cited by 0
- 2026CommunityFact: A Dynamic, Multilingual, Multi-domain Benchmark for Misinformation Detection in the Wildcited by 0
- 2026Better with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notescited by 0
- 2026Towards Multi-Agent-Simulation-Based Community Note Evaluationcited by 0
- 2026One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spreadcited by 0
- 2026CoVer: Conflict-Aware Claim Verificationcited by 0
- 2026CoVer: Conflict-Aware Claim Verification1 Sep 2026
- 2026One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spread31 Aug 2026
- 2026Towards Multi-Agent-Simulation-Based Community Note Evaluation3 Jun 2026
- 2026Better with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notes1 Jun 2026
- 2026CommunityFact: A Dynamic, Multilingual, Multi-domain Benchmark for Misinformation Detection in the Wild28 May 2026
- 2026The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformation15 Apr 2026
- 2026What do people want to fact-check?11 Feb 2026
- 2026GitSearch: Enhancing Community Notes Generation with Gap-Informed Targeted Search9 Feb 2026
- 2026Causally Disentangled Contrastive Learning for Multilingual Speaker Embeddings1 Feb 2026
- 2025Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation13 Oct 2025
- 2025Sword and Shield: Uses and Strategies of LLMs in Navigating Disinformation8 Jun 2025