# Agent Heterogeneity Mediates Extremism in an Adaptive Social Network Model

arXiv: https://arxiv.org/abs/2305.10230 · HTML: https://mlsanity.com/paper/2305.10230/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2023.

## Built on by (most cited first, 2 of 2)

- [Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy](https://mlsanity.com/paper/2411.06211/) (2024)
- [Problem-Solving in Language Model Networks](https://mlsanity.com/paper/2406.12374/) (2024)

## Abstract (arXiv)

An existing model of opinion dynamics on an adaptive social network is extended to introduce update policy heterogeneity, representing the fact that individual differences between social animals can affect their tendency to form, and be influenced by, their social bonds with other animals. As in the original model, the opinions and social connections of a population of model agents change due to three social processes: conformity, homophily and neophily. Here, however, we explore the case in which each node's susceptibility to these three processes is parameterised by node-specific values drawn independently at random from some distribution. This introduction of heterogeneity increases both the degree of extremism and connectedness in the final population (relative to comparable homogeneous networks) and leads to significant assortativity with respect to node update policy parameters as well as node opinions. Each node's update policy parameters also predict properties of the community that they will belong to in the final network configuration. These results suggest that update policy heterogeneity in social populations may have a significant impact on the formation of extremist communities in real-world populations.