研究によると、コミュニティノートはX上の虚偽情報の拡散を抑制するのに役立つ(Community Notes help reduce the virality of false information on X, study finds)

2025-09-18 ワシントン大学 (UW)

ワシントン大学主導の研究によると、X(旧Twitter)の「Community Notes」は誤情報の拡散を有効に抑制することが明らかになった。研究チームは2023年3月から6月にかけて約4万件の投稿を追跡し、ノートが付与されると48時間以内にリポストが平均46%、いいねが44%減少することを確認した。さらにリプライは22%、閲覧数は14%減少し、特に改変画像や動画を含む投稿や人気の高い投稿で効果が大きかった。一方で、ノート付与が48時間以上遅れると拡散抑制効果はほとんど消えることも分かった。研究者らは今後、ノート付与の迅速化を支援するツール開発を進める予定である。成果は PNAS に掲載された。

<関連情報>

コミュニティノートはオンライン上の虚偽情報への関与と拡散を減少させる Community notes reduce engagement with and diffusion of false information online

Isaac Slaughter, Axel Peytavin, Johan Ugander, and Martin Saveski
Proceedings of the National Academy of Sciences  Published:September 18, 2025
DOI:https://doi.org/10.1073/pnas.2503413122

研究によると、コミュニティノートはX上の虚偽情報の拡散を抑制するのに役立つ(Community Notes help reduce the virality of false information on X, study finds)

Significance

Warning labels about misinformation in social media posts are typically provided by professional fact-checkers. Recently, X introduced Community Notes, a feature enabling ordinary users to propose and vet fact-checking notes for potentially misleading posts. We examine the impact of these fact-checking notes on how users interact with noted posts. We find that once a note is attached, posts receive significantly fewer reposts, likes, replies, and views. We also observe significant changes in the statistical properties of the network paths noted posts take, indicating that the intervention alters how they diffuse within the social network. These results suggest that crowd-sourced fact-checking can be an effective tool for mitigating misinformation online, providing a valuable addition to efforts to combat its spread.

Abstract

Social networks scaffold the diffusion of information on social media. Much attention has been given to the spread of true vs. false content on online social platforms, including the structural differences between their diffusion patterns. However, much less is known about how platform interventions on false content alter the engagement with and diffusion of such content. In this work, we estimate the causal effects of Community Notes, a novel fact-checking feature adopted by X (formerly Twitter) to solicit and vet crowd-sourced fact-checking notes for false content. We gather detailed time series data for 40,078 posts for which notes have been proposed and use synthetic control methods to estimate a range of counterfactual outcomes. We find that attaching fact-checking notes significantly reduces the engagement with and diffusion of false content. We estimate that, on average, the notes resulted in reductions of 46.1% in reposts, 44.1% in likes, 21.9% in replies, and 13.5% in views after being attached. Over the posts’ entire lifespans, these reductions amount to 11.6% fewer reposts, 13.3% fewer likes, 6.9% fewer replies, and 5.5% fewer views on average. In reducing reposts, we observe that diffusion cascades for fact-checked content are less deep and less “viral,” but not less broad, than synthetic control estimates for non-fact-checked content with similar reach. This structural difference contrasts notably with differences between false vs. true content diffusion itself, where false information diffuses farther, but with structural patterns that are otherwise indistinguishable from those of true information, conditional on reach.

1600情報工学一般
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