The impact of scientific cooperation hypernetwork structure on research achievements: An empirical analysis

This study employs new network tools to reveal the relationship between the structure and function of scientific cooperation hypernetworks. Using data in the field of condensed matter physics, we model scientific cooperation hypernetworks with scholars as nodes and co-authored papers as hyperedges. By analyzing structural indicators (degree, betweenness, clustering coefficient), we observe significant heterogeneity in the hypernetworks. Through gray relational analysis, we identify the clustering coefficient as the most influential indicator for research achievements. Regression models further reveal that while higher node degree and betweenness enhance cooperative achievements, increased clustering coefficient suppresses cooperative achievements. These findings highlight structural trade-offs in optimizing scientific collaboration.