Patterns of Nonlinear Opinion Formation on Networks

Abstract

When communicating agents form opinions about a set of possible options, agreement and disagreement are both possible outcomes. Depending on the context, either can be desirable or undesirable. We show that for nonlinear opinion dynamics on networks, and a variety of network structures, the spectral properties of the underlying adjacency matrix fully characterize the occurrence of either agreement or disagreement. We further show how the corresponding eigenvector centrality, as well as any symmetry in the network, informs the resulting patterns of opinion formation and agent sensitivity to input that triggers opinion cascades.

6 pages, 4 figures; accepted to appear in 2021 American Control Conference proceedings

References in corpus (1)

• Analysis and control of agreement and disagreement opinion cascades

Cited by in corpus (4)

• Nonlinear Opinion Dynamics with Tunable Sensitivity
• Analysis and control of agreement and disagreement opinion cascades
• Switching transformations for decentralized control of opinion patterns in signed networks: application to dynamic task allocation
• Control of Agreement and Disagreement Cascades with Distributed Inputs