Analysis and prediction of the Horizon 2020 R&D&I collaboration network

Abstract

This study presents a novel link prediction model for the analysis and prediction of collaboration networks in the context of H2020 projects. This model incorporates various databases and expands the list of variables used in the analysis. In this study, the accuracy and interpretability of both generic and nongeneric link prediction algorithms are examined through a comprehensive analysis. Additionally, collaborative groups that exhibit stronger linkages than initially anticipated are examined, and their prevalence across different regions is evaluated. In this study, it was found that the collaboration network within H2020 has significant concentration and fragmentation levels. Moreover, several key factors that strongly influence collaboration, including prior and concurrent project involvement, earned contribution, and the economic and technological characteristics of participating businesses, were identified. This study additionally demonstrated that cooperative communities exhibit geographical concentration in western Europe, whereas nongeneric models offer improved predictive accuracy for identifying relationships. This research contributes to the field of cooperation network analysis and offers guidance to decision-makers on strategies to promote future collaborations in the context of FP.