Pith. sign in

REVIEW 2 cited by

Repulsive Bounded-Confidence Model of Opinion Dynamics in Polarized Communities

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2301.02210 v1 pith:LDN6MBNZ submitted 2023-01-05 math.DS

Repulsive Bounded-Confidence Model of Opinion Dynamics in Polarized Communities

classification math.DS
keywords opinionbounded-confidencedynamicsmodelmodelsopinionsindividualspeers
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

Collective opinions affect civic participation, governance, and societal norms. Due to the influence of opinion dynamics, many models of their formation and evolution have been developed. A commonly used approach for the study of opinion dynamics is bounded-confidence models. In these models, individuals are influenced by the opinions of others in their network. They generally assume that individuals will formulate their opinions to resemble those of their peers. In this paper, inspired by the dynamics of partisan politics, we introduce a bounded-confidence model in which individuals may be repelled by the opinions of their peers rather than only attracted to them. We prove convergence properties of our model and perform simulations to study the behavior of our model on various types of random networks. In particular, we observe that including opinion repulsion leads to a higher degree of opinion fragmentation than in standard bounded-confidence models.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. A Bounded-Confidence Model of Opinion Dynamics with Adaptive Interaction Probabilities

    physics.soc-ph 2026-05 unverdicted novelty 6.0

    An adaptive edge-weighted version of the DW opinion dynamics model is introduced with proven convergence properties and network-dependent effects on convergence time shown via simulations.

  2. A Bounded-Confidence Model of Opinion Dynamics with Adaptive Interaction Probabilities

    physics.soc-ph 2026-05 unverdicted novelty 6.0

    The authors extend the DW opinion dynamics model with adaptive edge weights on networks, prove convergence and effective-graph properties, and simulate that adaptive weights speed convergence on dense networks but slo...