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SOCIAL AND ECONOMIC PATTERNS OF PROTEST ACTIVITY IN RUSSIAN REGIONS: CURRENT DYNAMIC AND PROTEST POTENTIAL

A. Naydyonov

Abstract

Previous research in the field of protest activity showed that protests are result of a multifactorial impact of socio-economic factors on the individual and group consciousness of citizens, taking into account the cognitive and axiological refraction of the surrounding reality which differs drastically for different regions, time periods, other circumstances. The key finding is the fact that any protest activity is conditioned by nonlinear influence of social and economic factors which form particular patterns of protest activity due to the perception of personal and public well-being by individuals and groups of people. Thus, the periods of a similar state of the external environment and the level of economic performance can be characterized by different levels of protest moods in society. The aim of research is to build machine learning models which describe the process of formation of such patterns. Methodologically research is based on the welfare studies so far as protest activity is more connected with welfare due to the fact that marginal utility of goods determine inverse relationship between protest potential and welfare of population. In this work we have tried to design an approach which is based on the following assumptions: 1) the evaluation of the protest potential of the territory is determined on the basis of the function of summing up the protest potential of individuals, collectives or stratification groups, depending on the degree of presence or total absence of a particular kind of welfare, taking into account its marginal utility for an individual, collective or stratification group, respectively; 2) the integral calculation of the protest potential of the territory takes into account the revealed socio-economic patterns of the emergence of protest activity. Given the sample data we have build models (Decision Tree and Random Forest Regressions) in order to classify territories by protest activity and estimate composite indicator of protest potential in Russian regions.

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