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Russian Journal of Cybernetics, 2023, Volume 4, Issue 2, Pages 33–39
DOI: https://doi.org/10.51790/2712-9942-2023-4-2-05 (Mi uk54) 		 
Analysis of social media community posts

N. L. Avanesyana, V. V. Zenkovab, A. A. Chepovskiia, A. M. Chepovskiica

a Higher School of Economics, Moscow, Russian Federation
b Moscow Institute of Physics and Technology (MIPT), Dolgoprudny, Moscow Region, Russian Federation
c Peoples Friendship University of Russia, Moscow, Russian Federation
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DOI: https://doi.org/10.51790/2712-9942-2023-4-2-05
Abstract: The study is a statistical analysis of Telegram channels based on the correlation analysis of automatically generated frequency dictionaries. We presented the pairwise correlation factors for comparing the word frequency distribution in informal community posts. The method can identify informal communities by analyzing a graph built on the data exported from the Telegram messenger.
Keywords: social media analysis, informal graph communities, computerized analysis of texts, frequency dictionary, rank correlation.
Document Type: Article
Language: Russian
Citation: N. L. Avanesyan, V. V. Zenkova, A. A. Chepovskii, A. M. Chepovskii, “Analysis of social media community posts”, Russian Journal of Cybernetics, 4:2 (2023), 33–39
Citation in format AMSBIB
\Bibitem{AvaZenChe23}
\by N.~L.~Avanesyan, V.~V.~Zenkova, A.~A.~Chepovskii, A.~M.~Chepovskii
\paper Analysis of social media community posts
\jour Russian Journal of Cybernetics
\yr 2023
\vol 4
\issue 2
\pages 33--39
\mathnet{http://mi.mathnet.ru/uk54}
\crossref{https://doi.org/10.51790/2712-9942-2023-4-2-05}
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