Modeling confirmation bias and polarization

Online users tend to select claims that adhere to their system of belief= s and to ignore dissenting information. Confirmation bias, indeed, plays a = pivotal role in viral phenomena. Furthermore, the wide availability of cont= ent on the web fosters the aggregation of likeminded people where debates t= end to enforce group polarization. Such a configuration might alter the pub= lic debate and thus the formation of the public opinion. In this paper we p= rovide a mathematical model to study online social debates and the related = polarization dynamics. We assume the basic updating rule of the Bounded Con= fidence Model (BCM) and we develop two variations a) the Rewire with Bounde= d Confidence Model (RBCM), in which discordant links are broken until conve= rgence is reached; and b) the Unbounded Confidence Model, under which the i= nteraction among discordant pairs of users is allowed even with a negative = feedback, either with the rewiring step (RUCM) or without it (UCM). From nu= merical simulations we find that the new models (UCM and RUCM), unlike the = BCM, are able to explain the coexistence of two stable final opinions, ofte= n observed in reality. Lastly, we present a mean field approximation of the= newly introduced models.