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 the number of collaborations scales superlinearly with institution size, though 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 Zipfs law. These patterns can be reproduced by a simple model with three mechanisms: (i) researchers collaborate with friends-of-friends, (ii) new institutions trigger more potential institutions, and (iii) researchers are preferentially hired by large institutions. This model reveals an economy of scale in research: larger institutions grow faster and amplify collaborations. Our work provides a new understanding of emergent behavior in research institutions and how they facilitate innovation.
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