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 in terms of how many articles deserve platform actions but conservatives did prefer somewhat more action on content from liberal sources, and vice versa. We also find that judgments about two holistic properties, misleadingness, and harm, could serve as an effective proxy to determine what actions would be approved by a majority of raters.

Proceedings of the ACM on Human-Computer Interaction, Volume 7, Issue CSCW2, Article No.: 291, pp. 1–33

Access the paper here: https://doi.org/10.1145/3610082

— Shubham Atreja, Libby Hemphill, Paul Resnick