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Expressed and private opinion dynamics in signed networks based on path-dependence framework.

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Summary

This study explores how expressed and private opinions evolve in social networks. It finds that iterative discussions lead to alignment between private and expressed opinions, ensuring stability.

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Area of Science:

  • Social network dynamics
  • Opinion formation and evolution
  • Computational social science

Background:

  • Social networks exhibit complex opinion evolution, influenced by expressed and private opinions.
  • The tension between social conformity and individual authenticity shapes opinion dynamics.
  • Understanding opinion divergence and convergence is crucial in social network analysis.

Purpose of the Study:

  • To analyze opinion evolution in signed networks using the expressed and private opinion (EPO) model.
  • To investigate the impact of negative edges and topic transitions on opinion dynamics.
  • To derive conditions for consensus, stability, and alignment of expressed and private opinions.

Main Methods:

  • Application of the lifting technique to the EPO model to handle negative edges.
  • Utilization of path-dependence theory for modeling topic transitions.
  • Analytical derivation of conditions for opinion convergence and stability.
  • Numerical simulations for validation.

Main Results:

  • Sufficient conditions derived for eliminating discrepancies between expressed and private opinions.
  • Demonstrated convergence to zero consensus, bipartite consensus, or bounded opinion stability.
  • Established asymptotic alignment between private and expressed opinions through iterative discussions.
  • Identified a sufficient condition for bipartite consensus in structurally unbalanced networks.

Conclusions:

  • The EPO model provides a framework for understanding opinion dynamics considering both expressed and private opinions.
  • Iterative discussions can lead to opinion alignment and stability in social networks.
  • Network structure, particularly structural balance, significantly influences opinion convergence outcomes.