Remove, Reduce, Inform: What Actions do People Want Social Media Platforms to Take on Potentially Misleading Content?
Shubham Atreja, Libby Hemphill, Paul Resnick

TL;DR
This study investigates public preferences for social media actions on misinformation, revealing a general favor for informational labels over removal, with partisan differences influencing specific content actions.
Contribution
Provides empirical data on laypeople's preferences for platform actions on misinformation, highlighting the hierarchy of action severity and the influence of partisan bias.
Findings
Majority favor informational labels on most articles
Removal is preferred on the fewest articles
Partisan bias affects content action preferences
Abstract
To reduce the spread of misinformation, social media platforms may take enforcement actions against offending content, such as adding informational warning labels, reducing distribution, or removing content entirely. However, both their actions and their inactions have been controversial and plagued by allegations of partisan bias. When it comes to specific content items, surprisingly little is known about what ordinary people want the platforms to do. We provide empirical evidence about a politically balanced panel of lay raters' preferences for three potential platform actions on 368 news articles. Our results confirm that on many articles there is a lack of consensus on which actions to take. We find a clear hierarchy of perceived severity of actions with a majority of raters wanting informational labels on the most articles and removal on the fewest. There was no partisan difference…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
