He Said, She Said: Who Gets Believed When Spreading (Mis)Information - Nuzaina Khan; David Rand; Olga Shurchkov (Institute of Labor Economics (IZA), 2024)
We design an online experiment that mimics a Twitter/X "feed" to test whether (perceived) poster gender influences users' propensity to doubt the veracity of a given post. On average, posts by women are less likely to be flagged as concerning than identical posts by men. Heterogeneity analysis reveals that men are more likely to flag female-authored posts as the post's topic domain becomes more male-stereotyped. Female users do not exhibit the same bias. Actual post veracity, user ideology, and user familiarity with Twitter do not explain the findings. Flagging behavior on Twitter's crowdsourced fact-checking program is consistent with these findings.
Keywords: C90; D9; J16; L86; 330; gender differences; misinformation; economic experiments