Social Media Communities as an Example of a New Type of Communication Ecosystem and Society Clustering
Liu Z.-J. Abdullah N.B.T. Sokolovskiy K. Karabulatova I.
2025University of Texas Press
Information and Culture
2025#60Issue 158 - 78 pp.
The global proliferation of social networks exerts a significant influence on societal development in many countries worldwide. This study aims to conduct a comparative analysis of the key differences in social networks using China as a case study and to explore the global trends in the development of similar networks in other countries around the world. The methodology is based on Spanish sociologist Manuel Castells’s theory of network society. Using content analysis of the Sina Weibo social network, data on the hierarchical Dirichlet process were obtained, enabling the assessment of the thematic structure of user information, clustering, and segmentation of popular blogs.
hierarchy , machine learning , text mining , WeChat , Weibo
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Guangxi Normal University, China
Management and Science University, Malaysia
Department of General Subjects, Humanitarian and Technical Academy, Kokshetau, Kazakhstan
Laboratory of Machine Learning and Semantic Analysis, Institute of Artificial Intelligence, Lomonosov Moscow State University, Russian Federation
Institute of Russian Language, Heilongjiang University, China
Department of Foreign Languages, Philological Faculty, Lumumba RUDN University, Russian Federation
Guangxi Normal University
Management and Science University
Department of General Subjects
Laboratory of Machine Learning and Semantic Analysis
Institute of Russian Language
Department of Foreign Languages
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