Affective Polarization on Small-World and Scale-Free Networks

TL;DR

This paper models how social network structures like small-world and scale-free networks influence affective polarization, revealing that network topology impacts consensus formation and polarization dynamics.

Contribution

It provides a mean-field approximation of opinion dynamics on Watts-Strogatz and scale-free networks, linking network properties to polarization outcomes.

Findings

Power-law networks have fragile consensus stability.

Smaller average path length hinders consensus.

Model aligns with real-world network dynamics.

Abstract

Affective polarization, the emotional divide characterized by in-group love (trust towards fellow partisans) and out-group hate (mistrust towards those with opposite political views), has become prevalent in the current society. Despite its prevalence, the role of social network structure in the dynamics of affective polarization is yet to be well-understood. We provide a mean-field approximation of opinion dynamics under affective polarization on Watts-Strogatz and power-law (scale-free) networks. Our results show that consensus is fragile in social networks with power-law degree distributions, and the smaller average path length of the network (resembling a small-world network) makes achieving the consensus further difficult. Simulations and numerical experiments on real-world networks indicate that the mean-field model is aligned with the actual dynamics. Our findings shed light on how real-world network properties shape the dynamics of affective polarization and why consensus remains elusive in the real-world.