Analysis and control of agreement and disagreement opinion cascades

Alessio Franci, Anastasia Bizyaeva, Shinkyu Park, Naomi Ehrich Leonard

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce and analyze a continuous time and state-space model of opinion cascades on networks of large numbers of agents that form opinions about two or more options. By leveraging our recent results on the emergence of agreement and disagreement states, we introduce novel tools to analyze and control agreement and disagreement opinion cascades. New notions of agreement and disagreement centrality, which depend only on network structure, are shown to be key to characterizing the nonlinear behavior of agreement and disagreement opinion formation and cascades. Our results are relevant for the analysis and control of opinion cascades in real-world networks, including biological, social, and artificial networks, and for the design of opinion-forming behaviors in robotic swarms. We illustrate an application of our model to a multi-robot task-allocation problem and discuss extensions and future directions opened by our modeling framework.

Original languageEnglish (US)
Pages (from-to)47-82
Number of pages36
JournalSwarm Intelligence
Volume15
Issue number1-2
DOIs
StatePublished - Jun 2021

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Keywords

  • Centrality indices
  • Complex contagions
  • Networked control
  • Opinion dynamics
  • Robot swarms
  • Task allocation

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