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July 24, 2026
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Анализ текстов сообществ социальных сетей

Успехи кибернетики. 2023. Т. 4. № 2. С. 33–39.
Аванесян Н. Л., Зенькова В. В., Chepovskiy A., Chepovskiy A.

In this paper the authors describe the methodology for the statistical analysis of texts in the network of Telegram channels based on comparison of automatically generated frequency dictionaries by methods of correlation analysis. Coefficients of pairwise rank correlation are considered for comparing the frequency characteristics of texts in natural language. The method is proposed to assess the quality of the implicit communities extraction on the graph obtained by importing data from the channel network of the Telegram messenger.

Research target: Mathematics Computer Science
Language: Russian
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Keywords: анализ социальных сетейчастотный словарьfrequency dictionaryrank correlationsранговая корреляцияsocial networks analysisautomated text analysisавтоматический анализ текстовcommunities of graphнеявные сообщества графов
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