Approach to assessment of social media communities relationships based on text content thematic similarity (on the example of socially active fathers communities and communities with signs of radicalization)
Abstract
Automation of research on online radicalization is one of the urgent tasks of modern sociology. On the one hand, the availability of Internet data, including data from social networks, provides unique opportunities for the completeness of coverage of the phenomena and processes under study. On the other hand, despite the increased availability of Data Science tools, their use depends equally on both the relevant skills and competence in the applied subject area. The current work presents the experience of an interdisciplinary research group in adapting and applying tools for the automated collection and preprocessing of data on online radicalization. A toolkit for assessing the importance of words in posts based on the TF-IDF statistical measure is considered concerning the problem of assessing the relationships between communities of socially active fathers affiliated with the “Union of Fathers” and “Council of Fathers” organizations and communities with signs of radicalization belonging to various ideological platforms. The research was carried out based on open data of the social network “VKontakte”. Data collection is implemented using the social network API. The collection and processing of personal data were not carried out. The results of experimental testing showed the presence in some cases of stable relationships between the considered groups of communities. The results can be used in decision support processes when planning regional policies in relation to family and childhood and when planning measures to prevent destructive information and psychological impact.
About the Authors
A. O. Savelev
National Research Tomsk Polytechnic University
Russian Federation
Russian Federation
PhD in Technical Sciences, Associate Professor
A. Yu. Karpova
National Research Tomsk Polytechnic University
Russian Federation
Russian Federation
Doctor in Social Science, Professor
S. A. Kuznetsov
National Research Tomsk Polytechnic University
Russian Federation
Russian Federation
Engineer
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Review
For citations:
Savelev A.O., Karpova A.Yu., Kuznetsov S.A. Approach to assessment of social media communities relationships based on text content thematic similarity (on the example of socially active fathers communities and communities with signs of radicalization). Kazan economic vestnik. 2022;(1):96-103. (In Russ.)
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