  The spread of misinformation on social media is a pressing societal problem
that platforms, policymakers, and researchers continue to grapple with. As a
countermeasure, recent works have proposed to employ non-expert fact-checkers
in the crowd to fact-check social media content. While experimental studies
suggest that crowds might be able to accurately assess the veracity of social
media content, an understanding of how crowd fact-checked (mis-)information
spreads is missing. In this work, we empirically analyze the spread of
misleading vs. not misleading community fact-checked posts on social media. For
this purpose, we employ a dataset of community-created fact-checks from
Twitter's Birdwatch pilot and map them to resharing cascades on Twitter.
Different from earlier studies analyzing the spread of misinformation listed on
third-party fact-checking websites (e.g., Snopes), we find that community
fact-checked misinformation is less viral. Specifically, misleading posts are
estimated to receive 36.62% fewer retweets than not misleading posts. A partial
explanation may lie in differences in the fact-checking targets: community
fact-checkers tend to fact-check posts from influential user accounts with many
followers, while expert fact-checks tend to target posts that are shared by
less influential users. We further find that there are significant differences
in virality across different sub-types of misinformation (e.g., factual errors,
missing context, manipulated media). Moreover, we conduct a user study to
assess the perceived reliability of (real-world) community-created fact-checks.
Here, we find that users, to a large extent, agree with community-created
fact-checks. Altogether, our findings offer insights into how misleading vs.
not misleading posts spread and highlight the crucial role of sample selection
when studying misinformation on social media.
