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Opinion formation in multiplex networks with general initial distributions.

Chris G Antonopoulos1, Yilun Shang2

  • 1Department of Mathematical Sciences, University of Essex, Wivenhoe Park, UK. canton@essex.ac.uk.

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Summary

This study explores opinion dynamics on multiplex networks with varying confidence thresholds. Multiplexity can hinder consensus, especially with specific initial opinion distributions, offering insights into social dynamics.

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Area of Science:

  • Complex Systems
  • Network Science
  • Sociophysics

Background:

  • Opinion dynamics models often assume homogeneous confidence bounds among interacting agents.
  • Real-world social interactions occur on complex, multilayered networks with diverse agent characteristics.

Purpose of the Study:

  • To analyze opinion evolution on multiplex networks with heterogeneous confidence thresholds.
  • To determine critical thresholds for consensus formation under varying network structures and initial conditions.

Main Methods:

  • Analytical probability analysis to derive critical thresholds for consensus.
  • Numerical simulations on various network topologies (lattices, small-world, scale-free).
  • Investigation of structure-dependent convergence parameters for node heterogeneity.

Main Results:

  • Identified critical thresholds for phase transitions in long-term consensus behavior.
  • Revealed a quantitative relationship between critical thresholds and initial opinion distributions.
  • Observed that multiplexity can impede consensus formation within certain initial opinion ranges.

Conclusions:

  • The study provides analytical and numerical insights into opinion dynamics on multiplex networks.
  • Findings highlight the impact of network structure, confidence thresholds, and initial distributions on consensus.
  • Results offer valuable perspectives on information diffusion and social dynamics in complex multilayered systems.