Patterns of Nonlinear Opinion Formation on Networks

Anastasia Bizyaeva, Ayanna Matthews, Alessio Franci, Naomi Ehrich Leonard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2021 American Control Conference, ACC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2739-2744
Number of pages6
ISBN (Electronic)9781665441971
DOIs
StatePublished - May 25 2021
Externally publishedYes
Event2021 American Control Conference, ACC 2021 - Virtual, New Orleans, United States
Duration: May 25 2021May 28 2021

Publication series

NameProceedings of the American Control Conference
Volume2021-May
ISSN (Print)0743-1619

Conference

Conference2021 American Control Conference, ACC 2021
Country/TerritoryUnited States
CityVirtual, New Orleans
Period5/25/215/28/21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Multi-agent systems
  • consensus
  • decision making
  • graph theory
  • opinion dynamics

Fingerprint

Dive into the research topics of 'Patterns of Nonlinear Opinion Formation on Networks'. Together they form a unique fingerprint.

Cite this