Social Network Analysis (SNA) is a methodology and a theoretical perspective that studies patterns of relations among actors. When applied to the network of scientific collaborations at a university, SNA can provide many insights on the structure and the evolution of its scientific community.
Part I: Defining And Constructing The Social Network Of Scientific Collaborations At University Of Florida
A social network is a set of actors and the relations among them. Defining actors as researchers at UF, and relations as professional collaborations between researchers, we can use publicly availble data on publications and grants to visualize the social network of scientific collaborations at UF over the years. This reveals the structure of UF scientific community, and its interaction with formal organizations and institutional boundaries like departments, institutes and academic units.
Part II: Visualizing Group And Actor Characteristics In Collaboration Networks
Once we have network data on the UF scientific community, we can use SNA to visualize and analyze specific kinds of collaboration (e.g. publications vs grants); the position and centrality of particular departments, centers or institutes within UF’s scientific network; individual characteristics of UF researchers, be they network properties (e.g. actor centrality) or non-network attributes (e.g. researcher’s number of publications); the evolution of the UF scientific network over the years. SNA methods also allow us to detect cohesive subgroups(“communities”) of researchers who tend to work together in the university. Furthermore, the UF network can be aggregated from the individual level of researchers to the collective level of UF organizations, so as to visualize networks of collaborations among UF departments, institutes or academic units.