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

Abstract

Deploying links to professional fact-checking websites (so-called “snoping”) is a common misinformation intervention technique that can be used by social media users to refute misleading claims made by others. However, the real-world effect of snoping may be limited as it suffers from low visibility and distrust towards professional fact-checkers. As a remedy, X (formerly known as Twitter) recently launched its community-based fact-checking system “Community Notes” on which fact-checks are carried out by actual X users and directly shown on the fact-checked posts. Yet, an understanding of how fact-checking via Community Notes differs from regular snoping is largely absent. In this study, we empirically analyze differences in how contributors to Community Notes and Snopers select their targets when fact-checking social media posts. For this purpose, we collect and holistically analyze two unique datasets from X: (a) 25,912 community-created fact-checks from X's Community Notes platform, and (b) 52,505 “snopes” that debunk posts via fact-checking replies that link 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 emphasize the accuracy of non-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. From a practical perspective, our findings imply that different fact-checking approaches complement each other and may help social media providers to optimize strategies to combat misinformation on their platforms.