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Community Notes vs. Snoping: How the Crowd Selects Fact-Checking Targets on Social Media

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arxiv 2305.09519 v2 pith:VQ3TTKJM submitted 2023-05-16 cs.SI

classification cs.SI
keywords fact-checkingnotessocialmediacommunitypostscontributorssnopers
verification ladder T0 review T1 audit T2 compute T3 formal

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Deploying links to fact-checking websites (so-called "snoping") is a common intervention that can be used by social media users to refute misleading claims. However, its real-world effect may be limited as it suffers from low visibility and distrust towards professional fact-checkers. As a remedy, Twitter launched its community-based fact-checking system Community Notes on which fact-checks are carried out by actual Twitter users and directly shown on the fact-checked tweets. Yet, an understanding of how fact-checking via Community Notes differs from snoping is absent. In this study, we analyze differences in how contributors to Community Notes and Snopers select their targets when fact-checking social media posts. For this purpose, we analyze two unique datasets from Twitter: (a) 25,912 community-created fact-checks from Twitter's Community Notes platform; and (b) 52,505 "snopes" that debunk tweets via fact-checking replies linking to professional fact-checking websites. We find that Notes contributors and Snopers focus on different targets when fact-checking social media content. For instance, Notes contributors tend to fact-check posts from larger accounts with higher social influence and are relatively less likely to endorse/emphasize the accuracy of not misleading posts. Fact-checking targets of Notes contributors and Snopers rarely overlap; however, those overlapping exhibit a high level of agreement in the fact-checking assessment. Moreover, we demonstrate that Snopers fact-check social media posts at a higher speed. Altogether, our findings imply that different fact-checking approaches -- carried out on the same social media platform -- can result in vastly different social media posts getting fact-checked. This has important implications for future research on misinformation, which should not rely on a single fact-checking approach when compiling misinformation datasets.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 2 citations worldwide. Full citation record

  1. 'Debunk-It-Yourself': Health Professionals' Strategies for Responding to Misinformation on TikTok

    cs.CR 2024-12 conditional novelty 6.0 of 10

    Health professionals on TikTok debunk nutrition and mental health misinformation through a shared five-step process driven by perceived harm, scientific evidence, and symmetric duet-style responses.

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