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Dynamical modelling of street protests using the Yellow Vest Movement and Khabarovsk as case studies

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journal contribution
posted on 2023-01-20, 14:34 authored by Amer Alsulami, Anton Glukhov, Maxim Shishlenin, Sergei Petrovskii
Social protests, in particular in the form of street protests, are a frequent phenomenon of modern world often making a significant disruptive effect on the society. Understanding the factors that can affect their duration and intensity is therefore an important problem. In this paper, we consider a mathematical model of protests dynamics describing how the number of protesters change with time. We apply the model to two events such as the Yellow Vest Movement 2018–2019 in France and Khabarovsk protests 2019–2020 in Russia. We show that in both cases our model provides a good description of the protests dynamics. We consider how the model parameters can be estimated by solving the inverse problem based on the available data on protesters number at different time. The analysis of parameter sensitivity then allows for determining which factor(s) may have the strongest effect on the protests dynamics.

Funding

A.G. and M.S. was supported by the Mathematical Center in Akademgorodok (Novosibirsk), the agreement with Ministry of Science and High Education of the Russian Federation number 075-15-2019-1675. S.P. was supported by the RUDN University Strategic Academic Leadership Program.

History

Citation

Alsulami, A., Glukhov, A., Shishlenin, M. et al. Dynamical modelling of street protests using the Yellow Vest Movement and Khabarovsk as case studies. Sci Rep 12, 20447 (2022). https://doi.org/10.1038/s41598-022-23917-z

Author affiliation

School of Computing and Mathematical Sciences

Version

VoR (Version of Record)

Published in

SCIENTIFIC REPORTS

Volume

12

Pagination

20447

Publisher

NATURE PORTFOLIO

issn

2045-2322

eissn

2045-2322

Acceptance date

2022-11-07

Copyright date

2022

Available date

2023-01-20

Spatial coverage

England

Language

English

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