Right and left, partisanship predicts (asymmetric) vulnerability to misinformation

TL;DR

This study investigates how partisanship influences susceptibility to online misinformation on Twitter, revealing that both right- and left-leaning users are affected, with partisanship being the strongest predictor.

Contribution

The paper uncovers the asymmetric effects of partisanship on misinformation vulnerability and disentangles the influence of echo chambers through regression analysis.

Findings

Right-leaning users share more misinformation.

Left-leaning users also show increased vulnerability, but less so.

Partisanship is the strongest predictor of misinformation sharing.

Abstract

We analyze the relationship between partisanship, echo chambers, and vulnerability to online misinformation by studying news sharing behavior on Twitter. While our results confirm prior findings that online misinformation sharing is strongly correlated with right-leaning partisanship, we also uncover a similar, though weaker trend among left-leaning users. Because of the correlation between a user's partisanship and their position within a partisan echo chamber, these types of influence are confounded. To disentangle their effects, we perform a regression analysis and find that vulnerability to misinformation is most strongly influenced by partisanship for both left- and right-leaning users.