mlsanityData to 14 Oct 2026

Community Moderation and the New Epistemology of Fact Checking on Social Media

arXiv 2505.20067 ↗First posted 26 May 2025cs.SI cs.AI cs.CYcited by 5

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Abstract (arXiv)

Social media platforms have traditionally relied on internal moderation teams and partnerships with independent fact-checking organizations to identify and flag misleading content. Recently, however, platforms including X (formerly Twitter) and Meta have shifted towards community-driven content moderation by launching their own versions of crowd-sourced fact-checking -- Community Notes. If effectively scaled and governed, such crowd-checking initiatives have the potential to combat misinformation with increased scale and speed as successfully as community-driven efforts once did with spam. Nevertheless, general content moderation, especially for misinformation, is inherently more complex. Public perceptions of truth are often shaped by personal biases, political leanings, and cultural contexts, complicating consensus on what constitutes misleading content. This suggests that community efforts, while valuable, cannot replace the indispensable role of professional fact-checkers. Here we systemically examine the current approaches to misinformation detection across major platforms, explore the emerging role of community-driven moderation, and critically evaluate both the promises and challenges of crowd-checking at scale.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 25 of its 79 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

25 of 79 references.

References · 25

  1. 2021Automated Fact-Checking for Assisting Human Fact-Checkerscited by 144
  2. 2023Factuality Challenges in the Era of Large Language Modelscited by 126
  3. 2020That is a Known Lie: Detecting Previously Fact-Checked Claimscited by 82
  4. 2020Uncovering Coordinated Networks on Social Media: Methods and Case Studiescited by 49
  5. 2025Show Me the Work: Fact-Checkers' Requirements for Explainable Automated Fact-Checkingcited by 29
  6. 2023Fact-checking information from large language models can decrease headline discernmentcited by 22
  7. 2024Supernotes: Driving Consensus in Crowd-Sourced Fact-Checkingcited by 22
  8. 2022Birdwatch: Crowd Wisdom and Bridging Algorithms can Inform Understanding and Reduce the Spread of Misinformationcited by 21
  9. 2022Crowdsourced Fact-Checking at Twitter: How Does the Crowd Compare With Experts?cited by 16
  10. 2021Community-Based Fact-Checking on Twitter's Birdwatch Platformcited by 13
  11. 2024HateDay: Insights from a Global Hate Speech Dataset Representative of a Day on Twittercited by 13
  12. 2022Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harmscited by 10
13 more
  1. 2022Automated Content Moderation Increases Adherence to Community Guidelinescited by 10
  2. 2024Customized large language models can outperform Community Notes in correcting misinformationcited by 9
  3. 2025Can Community Notes Replace Professional Fact-Checkers?cited by 8
  4. 2019Social Influence and Unfollowing Accelerate the Emergence of Echo Chamberscited by 7
  5. 2022Diffusion of Community Fact-Checked Misinformation on Twittercited by 7
  6. 2024Who Checks the Checkers? Exploring Source Credibility in Twitter's Community Notescited by 6
  7. 2024Community Fact-Checks Trigger Moral Outrage in Replies to Misleading Posts on Social Mediacited by 4
  8. 2020Blackmarket-driven Collusion on Online Media: A Surveycited by 3
  9. 2025Assessing the Potential of Generative Agents in Crowdsourced Fact-Checkingcited by 3
  10. 2021Can crowdsourcing rescue the social marketplace of ideas?cited by 2
  11. 2024Political Fact-Checking Efforts are Constrained by Deficiencies in Coverage, Speed, and Reachcited by 2
  12. 2025References to unbiased sources increase the helpfulness of community fact-checkscited by 2
  13. 2017Factors in Recommending Contrarian Content on Social Mediacited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.