Measuring receptivity to misinformation at scale on a social media platform.

ABSTRACT: Measuring the impact of online misinformation is challenging. Traditional measures, such as user views or shares on social media, are incomplete because not everyone who is exposed to misinformation is equally likely to believe it. To address this issue, we developed a method that combines survey data with observational Twitter data to probabilistically estimate the number of users both exposed to and likely to believe a specific news story. As a proof of concept, we applied this method to 139 viral news articles and find that although false news reaches an audience with diverse political views, users who are both exposed and receptive to believing false news tend to have more extreme ideologies. These receptive users are also more likely to encounter misinformation earlier than those who

SUBMITTER: Tokita CK 

PROVIDER: S-EPMC11460357 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature