Yuwei Chuai, Moritz Pilarski, Thomas Renault, David Restrepo-Amariles, Aurore Troussel-Clément, Gabriele Lenzini, Nicolas Pröllochs
{"title":"基于社区的事实核查减少了误导性帖子在社交媒体上的传播","authors":"Yuwei Chuai, Moritz Pilarski, Thomas Renault, David Restrepo-Amariles, Aurore Troussel-Clément, Gabriele Lenzini, Nicolas Pröllochs","doi":"arxiv-2409.08781","DOIUrl":null,"url":null,"abstract":"Community-based fact-checking is a promising approach to verify social media\ncontent and correct misleading posts at scale. Yet, causal evidence regarding\nits effectiveness in reducing the spread of misinformation on social media is\nmissing. Here, we performed a large-scale empirical study to analyze whether\ncommunity notes reduce the spread of misleading posts on X. Using a\nDifference-in-Differences design and repost time series data for N=237,677\n(community fact-checked) cascades that had been reposted more than 431 million\ntimes, we found that exposing users to community notes reduced the spread of\nmisleading posts by, on average, 62.0%. Furthermore, community notes increased\nthe odds that users delete their misleading posts by 103.4%. However, our\nfindings also suggest that community notes might be too slow to intervene in\nthe early (and most viral) stage of the diffusion. Our work offers important\nimplications to enhance the effectiveness of community-based fact-checking\napproaches on social media.","PeriodicalId":501032,"journal":{"name":"arXiv - CS - Social and Information Networks","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Community-based fact-checking reduces the spread of misleading posts on social media\",\"authors\":\"Yuwei Chuai, Moritz Pilarski, Thomas Renault, David Restrepo-Amariles, Aurore Troussel-Clément, Gabriele Lenzini, Nicolas Pröllochs\",\"doi\":\"arxiv-2409.08781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Community-based fact-checking is a promising approach to verify social media\\ncontent and correct misleading posts at scale. Yet, causal evidence regarding\\nits effectiveness in reducing the spread of misinformation on social media is\\nmissing. Here, we performed a large-scale empirical study to analyze whether\\ncommunity notes reduce the spread of misleading posts on X. Using a\\nDifference-in-Differences design and repost time series data for N=237,677\\n(community fact-checked) cascades that had been reposted more than 431 million\\ntimes, we found that exposing users to community notes reduced the spread of\\nmisleading posts by, on average, 62.0%. Furthermore, community notes increased\\nthe odds that users delete their misleading posts by 103.4%. However, our\\nfindings also suggest that community notes might be too slow to intervene in\\nthe early (and most viral) stage of the diffusion. Our work offers important\\nimplications to enhance the effectiveness of community-based fact-checking\\napproaches on social media.\",\"PeriodicalId\":501032,\"journal\":{\"name\":\"arXiv - CS - Social and Information Networks\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Social and Information Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Social and Information Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
基于社区的事实核查是验证社交媒体内容和大规模纠正误导性帖子的一种很有前途的方法。然而,有关其在减少社交媒体上错误信息传播方面的有效性的因果证据还很缺乏。在此,我们进行了一项大规模的实证研究,分析社区注释是否减少了 X 上误导性帖子的传播。我们使用了差分法设计和 N=237,677 个(社区事实核查)级联的转贴时间序列数据,这些级联的转贴次数超过了 4.31 亿次,我们发现,让用户接触社区注释平均减少了 62.0% 的误导性帖子的传播。此外,社区注释还使用户删除其误导性帖子的几率提高了 103.4%。然而,我们的研究结果也表明,社区注释可能过于缓慢,无法在传播的早期(也是病毒最猖獗的阶段)进行干预。我们的工作为提高社交媒体上基于社区的事实核查方法的有效性提供了重要启示。
Community-based fact-checking reduces the spread of misleading posts on social media
Community-based fact-checking is a promising approach to verify social media
content and correct misleading posts at scale. Yet, causal evidence regarding
its effectiveness in reducing the spread of misinformation on social media is
missing. Here, we performed a large-scale empirical study to analyze whether
community notes reduce the spread of misleading posts on X. Using a
Difference-in-Differences design and repost time series data for N=237,677
(community fact-checked) cascades that had been reposted more than 431 million
times, we found that exposing users to community notes reduced the spread of
misleading posts by, on average, 62.0%. Furthermore, community notes increased
the odds that users delete their misleading posts by 103.4%. However, our
findings also suggest that community notes might be too slow to intervene in
the early (and most viral) stage of the diffusion. Our work offers important
implications to enhance the effectiveness of community-based fact-checking
approaches on social media.