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Feedback Loops in Opinion Dynamics of Agent-Based Models with Multiplicative Noise
Nataša Djurdjevac Conrad1, Jonas Köppl1,2, Ana Djurdjevac3
1Zuse Institute Berlin, 14195 Berlin, Germany.
Entropy (Basel, Switzerland)
|July 8, 2023
Summary
This study presents an agent-based model (ABM) simulating how opinions and social dynamics co-evolve. The model reveals how agent interactions and spatial proximity influence opinion formation and group behavior.
Area of Science:
- Computational Social Science
- Sociophysics
- Complex Systems
Background:
- Social dynamics and opinion formation are complex phenomena influenced by individual interactions.
- Understanding the interplay between agent mobility and opinion evolution is crucial for social science research.
Purpose of the Study:
- To introduce and analyze an agent-based model (ABM) for co-evolving opinions and social dynamics.
- To investigate the feedback loop between agent mobility and opinion dynamics.
- To explore emergent phenomena like group formation and opinion consensus.
Main Methods:
- Development of an agent-based model with agents possessing spatial positions and opinion states.
- Numerical simulations to study model behavior across different regimes.
- Formal analysis to derive a reduced model in the limit of infinite agents.
- Derivation of a partial differential equation (PDE) as a reduced model.
Main Results:
- The ABM captures the feedback loop between opinion dynamics and agent mobility.
- Emergent phenomena such as group formation and opinion consensus were observed.
- A PDE model was derived and shown to be a good approximation of the ABM.
Conclusions:
- The agent-based model provides a valuable framework for studying social dynamics and opinion co-evolution.
- The derived PDE offers a computationally efficient approximation for large-scale simulations.
- The research highlights the importance of spatial proximity and opinion similarity in shaping social structures.
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