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The HoneyComb Paradigm for Research on Collective Human Behavior

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Sociophysics Analysis of Multi-Group Conflicts.

Miron Kaufman¹, Hung T Diep², Sanda Kaufman³

¹Department of Physics, Cleveland State University, Cleveland, OH 44115, USA.

Entropy (Basel, Switzerland)

|December 8, 2020

Summary

This summary is machine-generated.

Statistical physics models reveal chaotic dynamics in multi-group social conflicts. These findings offer new strategies for conflict management and research by simulating realistic conflict scenarios.

Keywords:

complex systems mean-field theory monte carlo simulation social conflicts statistical physics approach

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Area of Science:

Statistical Physics
Social Sciences
Conflict Studies

Background:

Social conflicts involving multiple groups are complex and challenging to model.
Understanding the dynamics of group interactions is crucial for effective conflict resolution.

Purpose of the Study:

To apply statistical physics techniques to model multi-group social conflicts.
To develop realistic scenarios for conflict research and management strategies.
To investigate the role of interaction range in conflict dynamics.

Main Methods:

Identification of real-world conflict situations aligning with a statistical physics model.
Incorporation of realistic assumptions about conflict behaviors into model scenarios.
Analysis of two- and three-group conflict models.

Main Results:

Observed chaotic time evolution of mean attitudes within conflicting groups.
Identification of strange attractors, indicating complex, non-linear system behavior.
Demonstrated influence of interaction range on the emergence of chaotic dynamics.

Conclusions:

Statistical physics provides a powerful framework for analyzing complex social conflicts.
The developed models and scenarios can significantly inform conflict management strategies.
Understanding chaotic behavior and interaction ranges is key to predicting and mitigating social conflicts.