The desire to avoid cognitive dissonance drives community formation in a social network model
Year: 2025
Type: article
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.
Source: Scientific Reports
Authors: Zoltán Kovács, Gergely Palla, Anna Zafeiris
Institutions: Eötvös Loránd University, Semmelweis University
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,690
Awards: G113830941, G3423348113, G771654109
OpenAlex ID: W4417244203