# Opinion Polarization by Learning from Social Feedback

## TL;DR

This paper introduces a novel opinion dynamics model where social feedback influences polarization, demonstrating how groups can form strong opposing convictions through positive reinforcement in modular networks.

## Contribution

It presents an affective experience-based mechanism for polarization, analytically characterizing conditions for stable bi-polarization without relying on negative influence or bounded confidence.

## Key findings

- Strong convictions form in high modularity networks
- Positive social feedback reinforces opinions
- Bi-polarization stability conditions are analytically derived

## 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.