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STATISTICAL ANALYSIS OF THE SOCIAL TENSION FACTORS IN RUSSIA
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STATISTICAL ANALYSIS OF THE SOCIAL TENSION FACTORS IN RUSSIA
Annotation
PII
S042473880000616-6-1
Publication type
Article
Status
Published
Authors
Kirill Klimenko  Alexander Kudrov
ORCID: 0000-0003-2495-5496
Yuriy Gavrilets
ORCID: 0000-0002-5903-8674
Edition
Volume 52 Issue 1
Pages
45-66
Abstract
The behavior of the mass of the Russian population in the form of protest movements is discussed and analyzed. The hypothesis of political causation for the protests by terms of socio-economic life isn’t rejected. The empirical basis of the study are the data on protest activity of the population in 2011-2012 years, formed on the basis of printed and electronic federal and regional media as well as the content of social networking in Internet. It rantains mathematical and statistical analysis of various forms of public discontent and protests of various kinds. Two integral indexes are obtained from the principal component analysis: the index of social tension, which accumulates all kinds of protests, and index of social dissatisfaction, and which reflects all forms of discontent. The numerical values of these indices allow a comparison and ranking of different regions of Russia on the socio-political and economic environment. There is a statistically significant linear relationship shown between the two indices. The found regression makes it possible to carry out a conditional forecast of changes in social tension with changing certain indicators of social and economic discontent of the population.
Keywords
regions, protest movements, protests, social tensions, social discontent, the quality of living, the principal component analysis, regression analysis, conditional forecast
Date of publication
01.01.2016
Number of purchasers
1
Views
980
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0.0 (0 votes)
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Ajvazyan S., Bukhshtaber V., Enyukov I., Meshalkin L. (1989). Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti. M.: Finansy i statistika.         


Gavrilets Yu.N. (2014). Komp'yuternaya model' ideologicheskogo protivostoyaniya dvukh sil v obschestve // Ehkonomika i matematicheskie metody. T. 50. № 3. S. 73-85.                   


Gubanov D.A., Novikov D.A., Chkhartishvili A.G. (2010). Sotsial'nye seti: modeli informatsionnogo vliyaniya, upravleniya i protivoborstva. M.: Fizmatlit.           


Sobolev A. S. (2013). Faktory kollektivnogo dejstviya: sluchaj massovykh protestov v Rossii 2011-2012 gg. Preprint WP1/2012/05. M.: Vysshaya shkola ehkonomiki.         


Baldassarri D., Be arm an P.S. (2007). Dynamics of Political Polarization // American Sociological Review. Vol. 72 (5). R. 784-811.             


Cottle S. (2011). Reporting the Arab Uprisings: Notes // Research' Journalism: Theory, Practice and Criticism. Vol. 12(5). R. 647-659.            


Groshek J., Dimitrova D. (2011). A Cross Section of Voter Learning, Campaign Interest and Intention to Vote in the 2008 Presidential Election: Did Web 2.0 Matter? // Communication Studies. Vol. 9. R. 355-375.


Holland P.W., Welsch R.E. (1977). Robust Regression Using Iteratively Reweighted Least-Squares // Communications in Statistics: Theory and Methods. Vol. 1(1). R. 813-827.    


Howard P.N., Parks M.R. (2012). Social media and political change: Capacity, constraint, and consequence. Journal of Communication, 62, 359-362.    


Kaufhold K., Valenzuela S., Zuniga H.G. de (2010). Citizen Journalism and Democracy: How User-Generated News Use Relates to Political Knowledge and Participation // Journalism and Mass Communication            


Quarterly. Vol. 87(3-4) (Autumn/Winter). R. 515-529.    


Swigger N. (2012). The Online Citizen: Is Social Media Changing Citizens’ Beliefs about Democratic Values? Political Behavior. 18. DOI: 10.1007/s11109-012-9208-y

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