Network representations of diversity in scientific teams

Abstract

One strength of network analysis is its ability to encapsulate social heterogeneity. Here, we leverage that strength to examine another dimension of individual heterogeneity: heterogeneity of skills, knowledge and experience. This skill heterogeneity is difficult to quantify, but is vitally important to outcomes for both individuals and teams. Complicating the matter, skill diversity can be present on multiple levels. Individuals have different kinds of skills, but they also have different degrees of specialization. Skill diversity on a team level may come from individual skill diversity or focused researchers in different areas. Here, we illustrate our network-based method for characterizing skill sets in a context of increasing importance: scientific collaboration. Using data from the field of economics, we create network-based measures of paper scope, individual specialization, coauthor alignment and team skill diversity. We then use those measures to examine the relationship between skill diversity and publication outcomes.