The dynamics of social capital in scientific collaboration networks

Scientific collaboration is considered a cornerstone of 21st Century Science and a springboard for economic prosperity. At a more basic level, it is also considered to be a fundamental part of the development of scientific human capital. From that perspective, scientific collaboration is facilitated through social capital, which is acquired through an investment cycle. Through a series of collaborative interactions, scientists move to positions within collaboration networks, which in turn creates future opportunities for collaboration. Prior research has either focused on the positioning of scientists within their respective networks, or scientists' network activity and career stage, but few studies have looked at the dynamics of positioning due to the presence, timing, and sequencing of collaborative interactions on future opportunities. The reason for this gap was the intractability of the problem. In this paper, a research proposal is outlined that will attempt to address this deficiency by employing machine learning to identify patterns in the career trajectories of scientists in a research community.