Realtime user ratings as a strategy for combatting misinformation : an experimental study

Abstract

Fact-checking takes time. As a consequence, verdicts are usually reached after a message has started to go viral and interventions can have only limited effect. A new approach inspired by the scholarly debate and implemented in practice is to harness the wisdom of the crowd by enabling recipients of an online message to attach veracity assessments to it, with the intention to allow poor initial crowd reception to temper belief in and further spread of misinformation. We study this approach by letting 4,000 subjects in 80 experimental bipartisan communities sequentially rate the veracity of informational messages. We nd that in well-mixed communities, the public display of earlier veracity ratings indeed enhances the correct classi cation of true and false messages by subsequent users. However, crowd intelligence back res when false information is sequentially rated in ideologically segregated communities. This happens because early raters’ ideological bias, which is aligned with a message, in uences later raters’ assessments away from the truth. These results suggest that network segregation poses an important problem for community misinformation detection systems that must be accounted for in the design of such systems.