Can Community Notes Replace Professional Fact-Checkers?
Not on the map. Why?
Abstract (arXiv)
Two commonly employed strategies to combat the rise of misinformation on social media are (i) fact-checking by professional organisations and (ii) community moderation by platform users. Policy changes by Twitter/X and, more recently, Meta, signal a shift away from partnerships with fact-checking organisations and towards an increased reliance on crowdsourced community notes. However, the extent and nature of dependencies between fact-checking and helpful community notes remain unclear. To address these questions, we use language models to annotate a large corpus of Twitter/X community notes with attributes such as topic, cited sources, and whether they refute claims tied to broader misinformation narratives. Our analysis reveals that community notes cite fact-checking sources up to five times more than previously reported. Fact-checking is especially crucial for notes on posts linked to broader narratives, which are twice as likely to reference fact-checking sources compared to other sources. Our results show that successful community moderation relies on professional fact-checking and highlight how citizen and professional fact-checking are deeply intertwined.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 9 of its 53 references that are in the map. First posted on arXiv 19 Feb 2025.
Builds on
9 of 53 references.
References · 9
- 2023Factuality Challenges in the Era of Large Language Modelscited by 126
- 2025Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checkingcited by 29
- 2022Human and technological infrastructures of fact-checkingcited by 16
- 2022Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?cited by 16
- 2021Community-Based Fact-Checking on Twitter's Birdwatch Platformcited by 13
- 2024What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verificationcited by 10
- 2024Who Checks the Checkers? Exploring Source Credibility in Twitter's Community Notescited by 6
- 2024Community Fact-Checks Trigger Moral Outrage in Replies to Misleading Posts on Social Mediacited by 4
- 2023Community Notes vs. Snoping: How the Crowd Selects Fact-Checking Targets on Social Mediacited by 3
Built on by
Citing papers per year: 2025: 3; 2026: 5.
8 papers.
- 2025Community Moderation and the New Epistemology of Fact Checking on Social Mediacited by 5
- 2025COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanationscited by 5
- 2026The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformationcited by 2
- 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detectioncited by 1
- 2026Towards Multi-Agent-Simulation-Based Community Note Evaluationcited by 0
- 2026Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checkingcited by 0
- 2026One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spreadcited by 0
- 2026Community-Driven API and AI Writer Design for Openly Scaling Community Notescited by 0
- 2026Community-Driven API and AI Writer Design for Openly Scaling Community Notes30 Sep 2026
- 2026One AI Signal, Many Human Judgments: A Bayesian Cascade Analysis of AI-based Credibility Indicators in Online Information Spread31 Aug 2026
- 2026Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking2 Jul 2026
- 2026Towards Multi-Agent-Simulation-Based Community Note Evaluation3 Jun 2026
- 2026The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformation15 Apr 2026
- 2025COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations28 Oct 2025
- 2025The Psychology of Falsehood: A Human-Centric Survey of Misinformation Detection19 Sep 2025
- 2025Community Moderation and the New Epistemology of Fact Checking on Social Media26 May 2025