Big Egos in Big Science: Unlocking Peer and Status Effects in the Evolution of Collaborative Networks

In this paper we investigate the micro-mechanisms governing structural evolution and performance of scientific collaboration. Scientific discovery tends not to be lead by so called lone ?stars?, or big egos, but instead by collaboration among groups of researchers, from a multitude of institutions and locations, having a diverse knowledge set and capable of tackling more and more complex problems. This prose the question if Big Egos continues to dominate in this rising paradigm of big science. Using a dataset consisting of full bibliometric coverage from a Large Scale Research Facility, we utilize a stochastic actor oriented model (SAOM) to analyze both network endogeneous mechanisms and individual agency driving the collaboration network and further if being a Big Ego in Big Science translates to increasing performance. Our findings suggest that the selection of collaborators is not based on preferentialattachment, but more of an assortativity effect creating not merely a rich-gets-richer effect but an elitist network with high entry barriers. In this acclaimed democratic and collaborative environment of Big Science, the elite closes in on itself. We propose this tendency to be even more explicit in other knowledge producing environments with more visible boundaries and higher thresholds for collaboration.