FORMATION OF MULTI-UNIVERSITY SCIENTIFIC AND EDUCATIONAL COMMUNITIES BASED ON SCIENTOMETRIC ANALYSIS

The article examines the problem of forming multi-university scientific and educational communities based on scientometric and network analysis methods. A formal model for identifying inter-university collaborations is proposed, which is based on constructing a metric space of scientific publications and further clustering using the Louvain algorithm. The model makes it possible to represent universities and researchers as nodes of a collaboration network, where the edge weights are determined by the number of co-authored publications. The developed approach was applied to data from the open OpenAlexdatabase for the analysis of universities in Kazakhstan. The obtained results revealed the existence of a core of leading institutions (Al-Farabi Kazakh National University, Nazarbayev University, L. N. Gumilyov Eurasian National University, and Astana ITUniversity) that demonstrate the highest intensity of collaboration, while other universities remain at the periphery of the research network. It was also established that national collaborations in Kazakhstan are significantly stronger than internationalones, which highlights the need for further internationalization and integration into global scientific networks. The results obtained have both theoretical significance for the development of scientometrics and practical value for shaping science policy and designing strategies to improve the effectiveness of academic collaboration.