The Effects of Opinion Leader Radicalization Under Different User Tolerance Levels: Simulating Political Communications on Twitter

In this paper we present the results of computational experiments based on a novel agent-based communication model of Twitter activity. The model was designed specifically for analyzing the dynamics of communication between competing ideological positions, which sets the model apart from existing modelling literature. The model incorporates network structures into an agent-based framework; the nodes of the network represent regular users and political leaders. We also introduce network characteristics specific to Twitter, such as following and recommendations, the ability to view and retweet messages etc. Our model allows us to evaluate the effect of opinion and preference polarization, network homophily, radicalization of opinion leaders and user tolerance. In this study we specifically focus on radicalization and user tolerance. Based on 30 000 computational experiments, we show that changing user tolerance toward competing ideological positions changes substantively the propensity of opinion leaders to radicalize.