Resilience of Scientific Collaboration Networks in Young Universities Based on Bibliometric and Network Analysis
Kuchanskyi O. Andrashko Y. Biloshchytskyi A. Mukhatayev A. Biloshchytska S. Numanova F.
November 2025Multidisciplinary Digital Publishing Institute (MDPI)
Data
2025#10Issue 11
The resilience of scientific collaboration networks is a key factor in ensuring the long-term academic development of young universities. This study examines the resilience of scientific collaboration networks among young universities based on bibliometric and network analysis. Based on bibliometric data from the open database OpenAlex (as of September 2025, the database contains over 271 million scientific publications and 105 million authors), weighted undirected co-authorship graphs were constructed for four young universities from China, Kazakhstan, and the United Kingdom: Astana IT University, AITU (founded in 2019), Nazarbayev University, NU (2010), University of Suffolk, US (2007), and ShanghaiTech University, STU (2013). Key resilience indicators were calculated, including clustering coefficients, assortativity, modularity, and the dynamics of the largest connected component under different node removal scenarios. The study revealed that NU and STU have a highly resilient structure of scientific collaboration. AITU has been characterized by dynamic development and increasing resilience, particularly after 2023. The US network is fragmented and dependent on a small group of core researchers. However, despite its limited scale, it demonstrates a certain stability in preserving its core. Therefore, recommendations for the development of young universities have been formulated based on the research results. The findings highlight the importance of fostering horizontal scientific ties, deepening international cooperation, and developing long-term institutional strategies for young universities.
bibliometrics , co-authorship analysis , multi-university community , OpenAlex , resilience , scientific collaboration networks , scientometrics data , young universities
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School of Artificial Intelligence and Data Science, Astana IT University, Astana, 010000, Kazakhstan
Department of Information Control Systems and Technologies, Uzhhorod National University, Uzhhorod, 88000, Ukraine
Department of System Analysis and Optimization Theory, Uzhhorod National University, Uzhhorod, 88000, Ukraine
Department of Administration, Astana IT University, Astana, 010000, Kazakhstan
Department of Information Technology, Kyiv National University of Construction and Architecture, Kyiv, 03037, Ukraine
School of General Education Disciplines, Astana IT University, Astana, 010000, Kazakhstan
Higher School of Economics and Management, Turan University, Almaty, 050001, Kazakhstan
School of Artificial Intelligence and Data Science
Department of Information Control Systems and Technologies
Department of System Analysis and Optimization Theory
Department of Administration
Department of Information Technology
School of General Education Disciplines
Higher School of Economics and Management
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