Forecast of Socio-Political Instability (the Case of the Arab Spring)

Forecast of Socio-Political Instability (the Case of the Arab Spring)


Basaeva E.K.

Cand. Sci. (Physics and Mathematics), Head of the Department of Applied Mathematics and Computer Science, North Ossetian State University named after K.L. Khetagurov, Vladikavkaz, Russia. ek.basaeva@nosu.ru

Kamenetsky E.S.

Dr. Sci. (Physics and Mathematics), Head researcher, Southern Mathematics Institute VSC of RAS, Vladikavkaz, Russia. esk@smath.ru

Khosayeva Z.Kh.

Researcher, Vladikavkaz Science Center of RAS, Vladikavkaz, Russia. hzaiac83@mail.ru

ID of the Article:


This work was supported by the Ministry of Science and Higher Education of the Russian Federation (Agreement No. 075-02-2022-890).

Rubric: Political Sociology

For citation:

Basaeva E.K., Kamenetsky E.S., Khosayeva Z.Kh. Forecast of Socio-Political Instability (the Case of the Arab Spring). Sotsiologicheskie issledovaniya [Sociological Studies]. 2022. No 10. P. 96-106


 Full Text.


Abstract

The method for predicting conflict events based on the assumption of an increase in socio-political tension in the last years before the event is applied in the article. The sum of murders and suicides was taaken as an indicator of socio-political tension. A linear regression built on the values of the tension indicator over the past six years was used to reduce the impact of random fluctuations. It has been hypothesized that an increase in tension of more than 5% over five years could be a precursor of serious conflicts. The method was tested in the Arab countries during the events of the Arab Spring. The study showed that the growing socio-political tension in the Arab countries in 2005–2010 was associated with the ratio of the immigrants’ number to the permanent population. The share of immigrants less than 15% led to conflict, while that of over 15% reflected the tension of immigrants and, as a rule, did not lead to conflict. When using the suggested method for the Arab Spring events we are able to correctly predict the conflict in five out of six cases (probability of 83%) and a failed conflict was predicted in none of the cases. The accuracy of forecasts may be less for countries from other regions of the world while certain groups of countries may require additional indicators. It should be emphasized that the suggested method of forecasting might be used to predict unique conflicts.


Keywords
prediction of conflict; pre-cursor of conflict; socio-political tension; tension indicators; influence of immigrants on tensions; Arab spring

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Content No 10, 2022