MODELLING THE DYNAMICS OF SOCIAL PROTESTS: MEAN-FIELD GAMES AND INVERSE PROBLEMS

In recent years, there has been an increase in social tension all over the world, which manifests itself in the form of social protests. Understanding the dynamics of street protests and studying the factors that can influence their occurrence, duration and intensity is crucial for the stable and sustainable development of society. One of the approaches to constructing various scenarios of social dynamics is to use the theory of mean-field games. A combined mathematical model of social protests based on the approach of mid-level games and dynamic systems is proposed. Numerical results of solving the inverse problem based on statistical data of the social movement in France for 2018–2019 are presented.

Authors

Publication Details

Journal
Дифференциальные уравнения / Differential Equations
Published
2025-01-01
DOI
https://doi.org/10.7868/s3034503025060067
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
1.32
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article

MODELLING THE DYNAMICS OF SOCIAL PROTESTS: MEAN-FIELD GAMES AND INVERSE PROBLEMS

A. I. Glukhov
1 citations
Дифференциальные уравнения / Differential Equations
Opinion Dynamics and Social Influence
1.32
article

MODELLING THE DYNAMICS OF SOCIAL PROTESTS: MEAN-FIELD GAMES AND INVERSE PROBLEMS

A. I. Glukhov
article en
1 citations

Abstract

In recent years, there has been an increase in social tension all over the world, which manifests itself in the form of social protests. Understanding the dynamics of street protests and studying the factors that can influence their occurrence, duration and intensity is crucial for the stable and sustainable development of society. One of the approaches to constructing various scenarios of social dynamics is to use the theory of mean-field games. A combined mathematical model of social protests based on the approach of mid-level games and dynamic systems is proposed. Numerical results of solving the inverse problem based on statistical data of the social movement in France for 2018–2019 are presented.

Дифференциальные уравнения / Differential EquationsVol. 61(6)
Openalex Percentile: Top 16%
Opinion Dynamics and Social Influence
1.32
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