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arxiv: 2502.14132 · v2 · pith:SUGAJE2N · submitted 2025-02-19 · cs.CL · cs.AI

Can Community Notes Replace Professional Fact-Checkers?

Reviewed by Pith T0 review T1 audit T2 compute T3 formal T4 reserved pith:SUGAJE2Nrecord.jsonopen to challenge →

classification cs.CL cs.AI
keywords fact-checkingcommunitynotesprofessionalsourcesbroadermisinformationmoderation
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The Warrant Gap: Claim-Conditioned Re-scoring for Fact-Checking

    cs.CL 2026-06 unverdicted novelty 6.0

    Introduces claim-conditioned re-scoring (SIFT) and warranted supports proportion (WSP) metric, reporting accuracy recovery up to 27.6 points and WSP calibration at AUC 0.92 on FEVER, SciFact and other benchmarks.