Asks a user to rate the accuracy of the headline of a non-political news story.
Users exposed to this prompt go on to share higher-quality news sources.
They are also more selective about content they interact with on the platform—liking, commenting, higher quality posts and shares, &c.—for at least the following 24 hours.
The format can vary; this intervention was tested as a direct message to users on Twitter.
"We find clear evidence that the single accuracy message made users more discerning in their subsequent sharing decisions." write the authors of the study. "Relative to baseline, the accuracy message increased the average quality of the news sources shared, t(5378)=2.90, p=.004, and the total quality of shared sources summed over all posts, t(5378)=3.12, p=.002."
"This translates into increases of 4.8% and 9.0% respectively when estimating the treatment effect for user-days on which tweets would occur in treatment (that is, excluding user-days in the “never-taker” principal stratum[...] because the treatment cannot have an effect when no tweets would occur in either treatment or control); including user-days with no tweets yields an increase of 2.1% and 4.0%in average and total quality, respectively.
"Furthermore, the treatment more than tripled the level of sharing discernment (i.e., difference in number of mainstream versus fake/hyper-partisan links shared per user-day; interaction between post-treatment dummy and link type, t(5378)=3.27, p=.001)."
On top of the immediate effects for any given users, this has a cascading effect to their followers who in turn are exposed to less misinformation.
Improving the quality of the content shared by one user improves the content that their followers see, and therefore improves the content their followers share. This in turn improves what the followers’ followers see and share, and so on. Thus, the cumulative effects of such an intervention may be substantially larger than what is observed when only examining the treated individuals–particularly given that the treatment is as effective, if not more so, for users with larger numbers of followers.
Do you think this intervention could have more benefits, unacknowledged drawbacks, or other inaccuracies that we've neglected to mention here?
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