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Social Conflicts Studied by Statistical Physics Approach and Monte Carlo Simulations
Hung T. Diep * 1 , Miron Kaufman 2 , Sanda Kaufman 3
1  Laboratoire de Physique Théorique et Modélisation, University of Cergy-Pontoise, France.
2  Department of Physics, Cleveland State University, USA
3  Levin College of Urban Affairs, Cleveland State University, USA

10.3390/ecea-5-06661 (registering DOI)
Abstract:

Statistical physics models of social systems with a large number of members, each interacting with a subset of others, have been used in very diverse domains such as culture dynamics, crowd behavior, information dissemination and social conflicts. We observe that such models rely on the fact that large societal groups display surprising regularities despite individual agency. Unlike physics phenomena that obey Newton’s third law, in the world of humans the magnitudes of action and reaction are not necessarily equal. The effect of the actions of group n on group m can differ from the effect of group m on group n. We thus use the spin language to describe humans with this observation in mind. Note that particular individual behaviors do not survive in statistical averages. Only common characteristics remain. We have studied two-group conflicts as well as three-group conflicts. We have used time-dependent Mean-Field Theory and Monte Carlo simulations. Each group is defined by two parameters which express the intra-group strength of interaction among members and its attitude toward negotiations. The interaction with the other group is parameterized by a constant which expresses an attraction or a repulsion to other group average attitude. The model includes a social temperature T which acts on each group and quantifies the social noise. One of the most striking features is the periodic oscillation of the attitudes toward negotiation or conflict for certain ranges of parameter values. Other striking results include chaotic behavior, namely intractable, unpredictable conflict outcomes.

Keywords: social conflicts; statistical physics approach; complex systems; mean-field theory; Monte Carlo simulation
Comments on this paper
Luciano Costa
Opinion dynamics
Congratulations for the interesting work and presentation. This is certainly a subject of great interest, and the analyses you present seems to be well backed and general to me. Have you tried to test the effect of induced perturbations on the stability of the dynamics? Also, have you considered external fields or noise? We also work on opinions, and have recently studied how contrarian effects influences the appearance of social bubbles in complex network systems. In case you are interested:

https://www.researchgate.net/publication/336577243_Contrarian_effects_and_echo_chamber_formation_in_opinion_dynamics
All best wishes, Luciano Costa
Hung T. Diep
Reply to Prof. Costa's comment
Dear Dr. Costa,
Thank you very much for your interest in my work. Thanks a lot for informing me about your very interesting paper which uses also Statistical Physics in another way. We did not test yet effects of punctual perturbations for this problem of social conflicts, apart the bath of social temperature. Punctual perturbations including application of a field have meaning in real conflicts (a temporary measure from the international community for example).
I would like to take this opportunity to invite you to contribute a paper, or a review to the Special Issue

https://www.mdpi.com/journal/entropy/special_issues/Statis_Social where I am the Guest Editor. Please email me if you have questions about this.
Thanks a lot.
Best regards,
Hung T. Diep.

Hung T. Diep
Reply to Prof. Costa's comment
Dear Dr. Costa,
Thank you very much for your interest in my work. Thanks a lot for informing me about your very interesting paper which uses also Statistical Physics in another way. We did not test yet effects of punctual perturbations for this problem of social conflicts, apart the bath of social temperature. Punctual perturbations including application of a field have meaning in real conflicts (a temporary measure from the international community for example).
I would like to take this opportunity to invite you to contribute a paper, or a review to the Special Issue

https://www.mdpi.com/journal/entropy/special_issues/Statis_Social
where I am the Guest Editor. Please email me if you have questions about this.
Thanks a lot.
Best regards,
Hung T. Diep.

Feiyan Liu
Chaotic behavior
Thank you so much for your interesting paper, and it's very helpful to me.

BTW, have you tried to measure the chaotic behavior in social conflicts since you mentioned that it's a striking result in this paper.

Best Wishes, Feiyan Liu
Hung T. Diep
Thank you for your interest in my paper. I understand that you are working on this subject.
Please keep in touch.

For the chaotic behavior, we did not define a measure. We just observed the chaos from the simulation results. Maybe, a good way to study it is to analyze the chaotic oscillations by a time series. But we did not do that.

Also, in the 3-group conflict, we have seen the intractability with attractor lines, namely all points belonging to an attractor line are possible solutions.
This phenomenon can explain the unpredictible outcome in a conflict.
Best wishes.


 
 
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