A Time Series Analysis of Current and Future University Publication Collaborations
Abstract
Nowadays, university collaborations fundamentally determine the publication performance of universities. In our study, we examine the publication performance of the Hungarian university network in the period between 2015 and 2025. Using network indicators and time series clustering, we analyzed the current collaboration structure between universities. Subsequently, with the help of a gravity model, we determined the publication potentials of the universities, and then, in light of the gravity potentials and ETS forecasting, we proposed an optimal collaboration network for the year 2026. According to our results, the current university network is centralized. Universities with higher publication performance fundamentally determine the structure of collaborations and also belong to the same clusters over time, and their collaborations have a stabilizing effect on the network. Regarding future optimal collaborations, it is still advisable for these universities to collaborate with each other, while universities with lower publication performance also aim to catch up by collaborating with the higher-performing universities. The analysis highlighted that, in order to maximize publication performance, it is worthwhile to apply strategies that foster collaboration among institutions.
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