Opinion polarisation in social networks driven by cognitive dissonance avoidance

TL;DR

This paper presents an agent-based social network model demonstrating that the desire to avoid cognitive dissonance can lead to opinion polarization and community fragmentation, even from initially uniform societies.

Contribution

It introduces a novel model incorporating human-like belief systems and social connection tendencies to explain polarization dynamics.

Findings

Cognitive dissonance avoidance causes societal fragmentation.

Network parameters influence community structure diversity.

Polarization emerges from uniform initial conditions.

Abstract

As the consequences of opinion polarization effect our everyday life in more and more aspect, the understanding of its origins and driving forces becomes increasingly important. Here we develop an agent-based network model with realistic human traits: individuals in our simulations are endowed with an internal belief system which they attempt to keep as coherent as possible. This desire -- to reassure existing attitudes while avoiding cognitive dissonance -- is one of the most influential and widely accepted theories in social psychology by now. Our model shows that even in networks that start out completely uniform (from a society of clones), this effort leads to fragmentation and polarization, reflected both by the individual beliefs (attitudes) and the emerging communities in the social network. By fine-tuning two parameters: (i) "dissonance penalty", measuring the strength with which agents attempt to avoid cognitive dissonance, and (ii) "triadic closure affinity", the parameter reflecting agents' likelihood to connect with friends of friends, a wide range of possible community structures are observed.