Abstract
Societies tend to partition into factions based on shared beliefs, leading to sectarian conflict in soci-ety. This paper investigates mistrust as a cause for this partitioning by extending an established opinion dynamics model with Bayesian updating that specifies mistrust as the underlying mechanism for disagreement and, ultimately, polarisation. We demonstrate that mistrust is at the foundation of polarisation. Detailed analysis and the results of rigorous simulation studies provide new insight into the potential role of mistrust in polarisa-tion. We show that consensus results when mistrust levels are low, but introducing extreme agents makes consensus significantly harder to reach and highly fragmented and dispersed. These results also suggest a method to verify the model using real-world experimental or observational data empirically.
Highlights
Opinion Dynamics is the field of study interested in modelling opinion dissemination, how opinions spread from person to person and across a social network
The extended model follows the same trend as the two Martins models, but the extended model creates more opinion clusters
In this paper we have extended the model in Martins
Summary
If the information is consistent with what we already believe, the new information is deemed more likely to be true. Otherwise, if this latest information contradicts our current understanding, we are more likely to disregard it. If this latest information contradicts our current understanding, we are more likely to disregard it Psychology explains this phenomenon by appealing to the notion of cognitive dissonance and confirmation bias. . Cognitive dissonance results from new information conflicting with a person’s beliefs (Festinger ), causing psychological stress. . Mistrust of a source is a common reason to reject new information, implying that mistrust is a cause of confirmation bias.
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