Undergraduate researcher Dan Fortunato has been working this semester on a project to use ideas from condensed matter physics to study how researchers collaborate. This is part of an interdisciplinary area of considerable contemporary interest, where researchers have used quantitative tools from graph theory to gain quantitative information about all kinds of social networks. While people working in the field are typically interested in extracting generalities about human or animal behavior, we wondered what the approach could tell us about Tufts itself.
Dan describes the networks he calculated thus: (download the full version as a PDF)
“This is a graph visualization of the network of authors at Tufts. Nodes represent Tufts faculty, and connections are drawn between them if they have coauthored an academic paper together. Nodes are colored by department (with a legend supplied in the figure) and edge thickness is proportional to the number of papers coauthored between two people. Data was gathered from the PubMed database, which is why the Biomedical Engineering department is the best-represented department in the figure. The second page of the figure shows the graph sorted by department, so collaboration between departments is more apparent. One very prominent feature of the network is that many, many faculty members collaborate with David Kaplan (56 to be precise). Tufts is a very connected and tight-knit network, and as the graph demonstrates, collaboration is very prevalent in the Tufts community.”
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