Co-evolving networks for opinion and social dynamics in agent-based models

TL;DR

This paper introduces a stochastic agent-based model to study the co-evolution of opinions and social networks, capturing complex social phenomena like echo chambers and consensus, and applying it to real survey data.

Contribution

It presents a novel co-evolving opinion-social dynamics model that accounts for agents' mobility and interaction influences, filling a gap in existing literature.

Findings

Model captures emergence of echo chambers and consensus.

Application to survey data demonstrates real-world relevance.

Highlights importance of mutual influence in social and opinion dynamics.

Abstract

The rise of digital social media has strengthened the coevolution of public opinions and social interactions, that shape social structures and collective outcomes in increasingly complex ways. Existing literature often explores this interplay as a one-directional influence, focusing on how opinions determine social ties within adaptive networks. However, this perspective overlooks the intrinsic dynamics driving social interactions, which can significantly influence how opinions form and evolve. In this work, we address this gap, by introducing the co-evolving opinion and social dynamics using stochastic agent-based models. Agents' mobility in a social space is governed by both their social and opinion similarity with others. Similarly, the dynamics of opinion formation is driven by the opinions of agents in their social vicinity. We analyze the underlying social and opinion interaction networks and explore the mechanisms influencing the appearance of emerging phenomena, like echo chambers and opinion consensus. To illustrate the model's potential for real-world analysis, we apply it to General Social Survey data on political identity and public opinion regarding governmental issues. Our findings highlight the model's strength in capturing the coevolution of social connections and individual opinions over time.