How, When and Where Can Spatial Segregation Induce Opinion Polarization? Two Competing Models

Authored by Andreas Flache, Thomas Feliciani, Jochem Tolsma

Date Published: 2017

DOI: 10.18564/jasss.3419

Sponsors: No sponsors listed

Platforms: NetLogo

Model Documentation: Other Narrative Mathematical description

Model Code URLs: https://www.comses.net/codebases/4979/releases/1.0.0/

Abstract

Increasing ethnic diversity fosters scholarly interest in how the spatial segregation of groups affects opinion polarization in a society. Despite much empirical and theoretical research, there is little consensus in the literature on the causal link between the spatial segregation of two groups and the emergence of opinion polarization. We contribute to the debate by investigating theoretically the conditions under which the former fosters or hinders the latter. We focus on two processes of opinion polarization ( negative influence and persuasive argument communication) that, according to previous modelingwork, can be expected to make conflicting predictions about the relationship between segregation and opinion polarization. With a Schelling-type agent-based model of residential segregation, we generate initial environments with different levels of group segregation. Then we simulate the two processes of opinion dynamics. We show that the negative influence model predicts segregation to hinder the emergence of opinion polarization. On the other hand, the persuasive argument model predicts that segregation does not substantially foster polarization. Moreover, we explore how the spatial patterns of opinion distribution differs between the models: in particular, we investigate the likelihood that group membership and opinion align. We show that the alignment of group membership and opinions differs between the two opinion formation models, and that the scale at which we measure alignment plays a crucial role.
Tags
Social influence polarization Dynamics Segregation Opinion dynamics Attitudes computational model residential segregation Local convergence Team cohesion