Opinion Polarization by Learning from Social Feedback

Abstract

We explore a new mechanism to explain polarization phenomena in opinion dynamics in which agents evaluate alternative views on the basis of the social feedback obtained on expressing them. High support of the favored opinion in the social environment, is treated as a positive feedback which reinforces the value associated to this opinion. In connected networks of sufficiently high modularity, different groups of agents can form strong convictions of competing opinions. Linking the social feedback process to standard equilibrium concepts we analytically characterize sufficient conditions for the stability of bi-polarization. While previous models have emphasized the polarization effects of deliberative argument-based communication, our model highlights an affective experience-based route to polarization, without assumptions about negative influence or bounded confidence.

Presented at the Social Simulation Conference (Dublin 2017)

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• Enhanced Ability of Information Gathering May Intensify Disagreement Among Groups
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• Co-evolving networks for opinion and social dynamics in agent-based models
• The rise of populism and the reconfiguration of the German political space
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• Learning Interpretable Collective Variables for Spreading Processes on Networks
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