Comparative analysis of the peculiarities of news distribution in Chinese and Russian social networks

Abstract

This article is devoted to a comparative analysis of the features of news distribution in social networks of two major countries – China and Russia. The introduction describes the relevance of the research in the context of the globalization of the information space and the digitalization of mass communications, as well as differences in the cultural and political context that affect the methods and speed of news exchange in the online environment. The purpose of the study is to identify the key features of news distribution mechanisms in Chinese and Russian networks, identify similarities and differences, and assess the impact of these processes on the formation of public opinion and information flows. The Methods section describes the approaches and techniques used: comparative analysis, network analysis, content analysis of messages, as well as quantitative and qualitative research methods. The data was collected from leading social platforms specific to each country, which allowed for statistical processing and diagnostic evaluation of information patterns. The research is based on the analysis of big data, which ensures the objectivity and scalability of the results obtained. The Results section demonstrates that in Chinese social networks, news distribution is more centralized, with an emphasis on state control and algorithms that limit discursive diversity, while Russian networks are characterized by more decentralized information dissemination schemes with a high degree of user engagement and significant influence from independent sources. The features of time trends and dynamics of user reactions are also revealed, which emphasizes the importance of cultural and political factors. The "Discussion" section provides an interpretation of the results, taking into account the specifics of the information policy and media space of both countries. The prospects for further research aimed at developing models for predicting the dynamics of news distribution in various political and cultural settings are discussed, and practical recommendations for optimizing communication strategies in social networks are indicated. The work contributes to the understanding of the transnational dynamics of media processes and stimulates interdisciplinary research in the field of information technology and sociology.