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Anisotropic opinion dynamics.

Juan Neirotti1

  • 1Department of Mathematics, Aston University, The Aston Triangle, B4 7ET, Birmingham, United Kingdom.

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Summary
This summary is machine-generated.

Agents with adaptive neural networks exhibit conservative or liberal opinions based on peer influence. Varying this influence reveals opinion hysteresis, disappearing with high social influence variance.

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Area of Science:

  • Computational Social Science
  • Sociophysics
  • Artificial Intelligence

Background:

  • Opinion formation is a complex social process.
  • Adaptive agents and network topology influence societal dynamics.

Purpose of the Study:

  • To model opinion formation in a society of interacting agents.
  • To investigate the impact of peer influence on agent attitudes (conservative vs. liberal).
  • To analyze the emergence of hysteresis in social opinion.

Main Methods:

  • Agents represented by adaptive neural networks.
  • Network topology modeled using graph theory.
  • Online learning framework for continuous adaptation.
  • Statistical mechanics techniques to derive system dynamics.

Main Results:

  • Agents exhibit conservative or liberal attitudes based on peer influence.
  • Varying average peer influence induces hysteresis in average social opinion.
  • Hysteretic behavior diminishes with increased social influence variance.
  • Transition to liberal behavior involves the formation of conservative clusters.

Conclusions:

  • Social opinion dynamics can exhibit hysteresis under controlled peer influence.
  • The variance of social influence is critical in determining hysteretic behavior.
  • Conservative clusters emerge during transitions, indicating leader-follower dynamics in opinion shifts.