Shared Partisanship Dramatically Increases Social Tie Formation in a Twitter Field Experiment

Abstract

Americans are much more likely to be socially connected to co-partisans, both in daily life and on social media. But this observation does not necessarily mean that shared partisanship per se drives social tie formation, because partisanship is confounded with many other factors. Here, we test the causal effect of shared partisanship on the formation of social ties in a field experiment on Twitter. We created bot accounts that self-identified as people who favored the Democratic or Republican party, and that varied in the strength of that identification. We then randomly assigned 842 Twitter users to be followed by one of our accounts. Users were roughly three times more likely to reciprocally follow-back bots whose partisanship matched their own, and this was true regardless of the bot’s strength of identification. Interestingly, there was no partisan asymmetry in this preferential follow-back behavior: Democrats and Republicans alike were much more likely to reciprocate follows from co-partisans. These results demonstrate a strong causal effect of shared partisanship on the formation of social ties in an ecologically valid field setting, and have important implications for political psychology, social media, and the politically polarized state of the American public.

Cognitive reflection correlates with behavior on Twitter

“…It would be fruitful for future theoretical work to model cognition and networks in the context of co-follower networks, rather than the direct connections considered in past work. Future work should also use field experiments examining link formation and reciprocity on social media 68 to test for causal effects of shared cognitive style on following behavior.…”

Shifting attention to accuracy can reduce misinformation online

“…Why, then, were the participants in study 1-along with millions of other American people in recent years-willing to share misinformation? In answer, we advance the inattention-based account, in which (i) people do care more about accuracy than other content dimensions, but accuracy nonetheless often has little effect on sharing, because (ii) the social media context focuses their attention on other factors such as the desire to attract and please followers/friends or to signal one's group membership [23][24][25] . In the language of utility theory, we argue that an 'attentional spotlight' is shone upon certain terms in the decider's utility function, such that only those terms are weighed when making a decision (for a mathematical formalization of this limited-attention utility model, see Supplementary Information section 3).…”

Strategic identity signaling in heterogeneous networks

“…Our study reflects the complexity of how strategies of identity signaling can vary across communities and time. In the real world, including Twitter, communities are highly assortative and individuals can often restrict interaction partners to members of their ingroups (Bishop, 2009;Bakshy et al, 2015;Mosleh et al, 2021). Twitter networks therefore tend to be segregated, with conversations mostly occurring within coarse-grained political groups.…”