Promoting a Leader or a Cause? An Agent-Based Model of Social Media Bots

Abstract

Automated social media accounts, a.k.a. social media bots, have been gaining increasing interest among scholars studying human online behavior in recent years. Despite the abundant literature on bots, their substantive effects remain understudied. This paper bridges the existing gap by developing a realistic computational model of human interactions on Twitter, a popular social media platform, that includes leaders, ordinary users, and bots attached to leaders. First, we employ this model to study the effects of bots with different functions on promoting their leader by gaining them extra followers or retweets. Second, we explore the effects of bots on promoting their leader’s cause through increasing the volume of tweets with the leader’s ideology. We show that bots can be detrimental to the leaders’ personal popularity, whereas the effect on cause promotion depends on the distribution of bots among leaders. These results can be used for developing suitable research designs for further empirical estimation of the effects of bots.

Acknowledgments. The research was supported by RSF (project No. 20-18-00274), HSE University.