Big Data as a source of sociological information: the analysis of the blog by Saint Petersburg’s governor

Release:

2019, Vol. 3. №3

Title: 
Big Data as a source of sociological information: the analysis of the blog by Saint Petersburg’s governor


For citation: Maltseva A. V., Matveev M. S., Moiseeva M. B. 2019. “Big Data as a source of sociological information: the analysis of the blog by Saint Petersburg’s governor”. Siberian Socium, vol. 3, no 3, pp. 74-84. DOI: 10.21684/2587-8484-2019-3-3-74-84

About the authors:

Anna V. Maltseva, Dr. Sci. (Soc.), Associate Professor, Department of Social Analysis and Mathematical Methods on Sociology, Saint Petersburg State University (Saint Petersburg, Russian Federation); eLibrary AuthorID, ORCID, Web of Science ResearcherID, Scopus AuthorID, Google Scholarannamaltseva@rambler.ru

Mikhail S. Matveev, Undergraduate Student, Saint Petersburg State University (Saint Petersburg, Russian Federation); eLibrary AuthorID, ORCID, Web of Science ResearcherID, mikhail.matveev97@gmail.com

Maria B. Moiseeva, Undergraduate Student, Saint Petersburg State University (Saint Petersburg, Russian Federation); mariamoiseeva108@gmail.com

Abstract:

This article explores the possibilities of Big Data in forecasts and social networks as a source of information about society, as well as its role in security processes. The authors aim to study the possibility of obtaining socially significant information through Big Data, in particular, on one of the aspects of environmental safety. Fundamental sociological theories are considered, such as theories of the risk society by W. Beck and E. Giddens, as well as the information society (accounting for the peculiarities of the influence of the latest information technologies on society, including Big Data). Based on a number of studies systematizing approaches to the definition of Big Data, the authors derive their own. Using qualitative methods (in particular, content analysis), the authors analyzed the example of the incident-management application provided by the Committee on Informatization and Communications of the City of Saint Petersburg. The empirical base of the study includes 16,694 comments on the public page of the governor of St. Petersburg Alexander Beglov, obtained through a program in Python and using VK Api. The study analyzes user comments on environmental risks in the districts of St. Petersburg, identifies areas that are most exposed to environmental risks, as well as the sources of these risks and the subjects of responsibility for them. The results show that informal means of communication between representatives of the executive branch and citizens are of great interest as a source of sociological information investigated using algorithms and methods for analyzing Big Data. Such analysis helps in increasing security by reducing uncertainty and gaining new knowledge about society. On the other hand, the researchers have identified possible social risks associated with collecting, storing, and using Big Data. In particular, these are the risks of external interference with the application. In practice, these risks should be prevented and minimized by improving and testing applications by the developing company. Sociology, in turn, must consider this fact and avoid introducing undue errors in the research results.

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