A Psychologically-Motivated Model of Opinion Change with Applications to American Politics

Authored by Peter Duggins

Date Published: 2017

DOI: 10.18564/jasss.3316

Sponsors: No sponsors listed

Platforms: Python

Model Documentation: Other Narrative Mathematical description

Model Code URLs: https://github.com/psipeter/isc

Abstract

gent-based models are versatile tools for studying how societal opinion change, including political polarization and cultural diffusion, emerges from individual behavior. This study expands agents' psychological realism using empirically-motivated rules governing interpersonal influence, commitment to previous beliefs, and conformity in social contexts. Computational experiments establish that these extensions produce three novel results: (a) sustained ``strong{''} diversity of opinions within the population, (b) opinion subcultures, and (c) pluralistic ignorance. These phenomena arise from a combination of agents' intolerance, susceptibility and conformity, with extremist agents and social networks playing important roles. The distribution and dynamics of simulated opinions reproduce two empirical datasets on Americans' political opinions.

Tags

Agent-based model Social networks polarization Dynamics Opinion dynamics extremism Norms Network conformity Social-influence Local convergence Attitude-change Biased assimilation Pluralistic ignorance Repulsion hypothesis