The emergence of heterogeneous scaling in research institutions

2021 
Research institutions provide the infrastructure for scientific discovery, yet their role in the production of knowledge is not well characterized. To address this gap, we analyze interactions of researchers within and between institutions from millions of scientific papers. Our analysis reveals that collaborations densify as each institution grows, but at different rates (heterogeneous densification). We also find that the number of institutions scales with the number of researchers as a power law (Heaps’ law) and institution sizes approximate Zipf’s law. These patterns can be reproduced by a simple model in which researchers are preferentially hired by large institutions, while new institutions complimentarily generate more new institutions. Finally, new researchers form triadic closures with collaborators. This model reveals an economy of scale in research: larger institutions grow faster and amplify collaborations. Our work deepens the understanding of emergent behavior in research institutions and their role in facilitating collaborations. The scientific ecosystem is characterized by complex multifaceted relationships between institutions, researchers, and their collaborators. In this work, the authors find common patterns in these relationships expressed through superlinear scaling, Heaps’ law, and Zipf’s law within the global collaboration network, and propose a minimal network model to explain these patterns based on preferential hiring by larger institutions, the “adjacent possible” capturing the birth of new institutions, and triadic closure of collaborations.
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