Male online community. Topic modeling and content analysis
https://doi.org/10.28995/2073-6401-2025-4-153-162
Abstract
The article presents the results of a study on a male online community as one of the forms of the institution of male unions, performing the function of socialization and emotional mutual support for males. From the discourse analysis point of view, the male online community is analyzed as a discourse of masculinity, within which a certain model of masculinity is produced and supported, which includes the ideal of behavior, norms and values recognized as adequate for a modern man. The work contains a quantitative analysis of a large array of text data collected by the web scraping method, preprocessed for quantitative research. The methodological basis of the analysis consisted of content analysis and thematic modeling using Latent Dirichlet Allocation (LDA).
Qualitative discourse analysis is an auxiliary method for clarifying the findings. Following the study, the author identifies several blocks of topics existing within the discourse of the male online community. As well as he shows the relationship between gender processes occurring in modern Russian society and the topics and issues discussed within the selected male online community. Methodological conclusions on the application of topic modeling to large text data are presented.
About the Author
A. V. TerekhovРоссия
Aleksey V. Terekhov, postgraduate student
bldg. 1, bld. 82, Vernadskii Avenue, Moscow, 119606
References
1. Almaev, N.A. and Murasheva, O.V (2022), “Thematic analysis of discussions using the latent Dirichlet allocation], Institute of Psychology Russian Academy of Sciences. Social and Economic Psychology, no. 1 (25), Moscow, Russia, pp. 47–69.
2. Fairclough, N. and Wodak, R. (1997), “Critical discourse analysis: An overview”, T. van Dijk (ed.), Discourse and Interaction, Sage, London, UK, pp. 67–97.
3. Komarova, A.V. (2018), “The subculture of male unions as a socio-cultural institution in modern societies”, Observatory of Culture, vol. 15, no. 6, pp. 740–753.
4. Sievert, C. and Shirley, K. (2014), “LDAvis: A method for visualizing and interpreting topics”, Proceedings of the workshop on interactive language learning, visualization, and interfaces, Baltimore, USA, pp. 63–70.
5. Terekhov, A.V. (2023), “Male online-communities. Conceptual analysis and research perspectives”, Bulletin of the South Russian State Technical University. Series: Socioeconomic Sciences, vol. 16, no. 5 (16), pp. 81–90.
6. Tong, Z. and Zhang, H. (2016). “A text mining research based on LDA topic modelling”, International conference on computer science, engineering and information technology, Wolfville, NS, Canada, pp. 201–210.
Review
For citations:
Terekhov A.V. Male online community. Topic modeling and content analysis. RSUH/RGGU BULLETIN. Series Philosophy. Social Studies. Art Studies. 2025;(4):153-162. (In Russ.) https://doi.org/10.28995/2073-6401-2025-4-153-162
JATS XML
















