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Collective opinions affect civic participation, governance, and societalnorms. Due to the influence of opinion dynamics, many models of their formationand evolution have been developed. A commonly used approach for the study ofopinion dynamics is bounded-confidence models. In these models, individuals areinfluenced by the opinions of others in their network. They generally assumethat individuals will formulate their opinions to resemble those of theirpeers. In this paper, inspired by the dynamics of partisan politics, weintroduce a bounded-confidence model in which individuals may be repelled bythe opinions of their peers rather than only attracted to them. We proveconvergence properties of our model and perform simulations to study thebehavior of our model on various types of random networks. In particular, weobserve that including opinion repulsion leads to a higher degree of opinionfragmentation than in standard bounded-confidence models.

Repulsive Bounded-Confidence Model of Opinion Dynamics in Polarized Communities