Consensus in the Hegselmann–Krause Model

Nicolas Lanchier, Hsin Lun Li

Research output: Contribution to journalArticlepeer-review

Abstract

This paper is concerned with the probability of consensus in a multivariate, socially structured version of the Hegselmann–Krause model for the dynamics of opinions. Individuals are located on the vertices of a finite connected graph representing a social network, and are characterized by their opinion, with the set of opinions Δ being a general bounded convex subset of a finite dimensional normed vector space. Having a confidence threshold τ, two individuals are said to be compatible if the distance (induced by the norm) between their opinions does not exceed the threshold τ. Each vertex x updates its opinion at rate the number of its compatible neighbors on the social network, which results in the opinion at x to be replaced by a convex combination of the opinion at x and the nearby opinions: α times the opinion at x plus (1 - α) times the average opinion of its compatible neighbors. The main objective is to derive a lower bound for the probability of consensus when the opinions are initially independent and identically distributed with values in the opinion set Δ.

Original languageEnglish (US)
Article number20
JournalJournal of Statistical Physics
Volume187
Issue number3
DOIs
StatePublished - Jun 2022

Keywords

  • Confidence threshold
  • Consensus
  • Hegselmann–Krause model
  • Interacting particle systems
  • Martingale
  • Martingale convergence theorem
  • Opinion dynamics
  • Optional stopping theorem
  • Primary 60K35

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Mathematical Physics

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