How Gullible Are You? Predicting Susceptibility to Fake News

Tracy Jia Shen, Robert Cowell, Aditi Gupta, Thai Le, Dongwon Lee, Amulya Yadav

Abstract

In this research, we hypothesize that some social users are more gullible to fake news than others, and accordingly investigate on the susceptibility of users to fake news–i.e., how to identify susceptible users, what are their characteristics, and if one can build a prediction model.Building on the crowdsourced annotations of 5 types of susceptible users in Twitter, we found out that: (1) susceptible users are correlated with a combination of user, network, and content features; (2) one can build a reasonably accurate prediction model with 0.82 in AUC-ROC for the multinomial classification task; and (3) there exists a correlation between the dominant susceptibility level of center nodes and that of the entire network.