Opinion dynamics on switching networks

TL;DR

This paper investigates how the varying activation frequencies of different layers in a directed multilayer network influence the convergence of opinion dynamics, with implications for understanding complex social interactions.

Contribution

It introduces a model for opinion dynamics on multilayer networks with time-varying adjacency matrices, analyzing the impact of layer activation frequencies on convergence behavior.

Findings

Layer activation frequency significantly affects convergence speed.

The model accounts for in-degree proportional influence among agents.

Insights applicable to multilayer social and communication networks.

Abstract

We study opinion dynamics over a directed multilayer network. In particular, we consider networks in which the impact of neighbors of agents on their opinions is proportional to their in-degree. Agents update their opinions over time to coordinate with their neighbors. However, the frequency of agents' interactions with neighbors in different network layers differs. Consequently, the multilayer network's adjacency matrices are time-varying. We aim to characterize how the frequency of activation of different layers impacts the convergence of the opinion dynamics process.