For the privacy of my subjects, I’ve anonymized this group, but I can tell you that they are a multidisciplinary clean energy group at a major American university. I got a list of group members from their public web site, and then scraped Web of Science for their publications. After some preliminary data cleaning, I produced this network.
As for clearing away excess information, we could look at just the core of the research group, the people officially listed on the roster, but this may pare us down too far.
Since one of the focuses of the grant is graduate student training, we should focus on the grad students, indicated with white bullseyes. ANON 2 has authored papers with 5 grad students, as has ANON 20 and ANON 27, but a closer examination reveals they have mostly authored with their own grad students.
ANON 7, ANON 23, ANON 33, ANON 34, ANON 37 have coauthored papers with multiple professors on the grant. They might be students who have been around longer and so have had time to work with professors, or they might be more ambitious than is typical. It’d be interesting to check, if I were doing this properly and not as an illustrative example. Looking at the islands not connected to the main component, three of them consist of grad students. I believe these people conducted research as undergrads, and have not yet published papers in grad school as part of this institution's network. Several of the students haven’t published at all, and so aren’t on the map. Finally, ANON 42, ANON 57, and ANON 97 are not members of the group, but have published with three or more group professors. They might be worth investigating.
Another stated goal of this group is interdisciplinary integration. One measure that the field has settled on is the Rao-Stirling diversity index, as calculated by Cassi et al (2014 & 2017), which serves as proxy for knowledge integration. To put it simply (and gloss over some details), every article is assigned to one or more Web of Science categories, and cites many other papers which are also in Web of Science categories. A good measure of diversity requires a distance measure between Web of Science categories, which is provided provided by Rafols et al 2009. Run the math, and you can pick out more interdisciplinary and integrated scholars in a heatmap. I’ve used to same technique to indicate more unusual collaborations.
ANON 1 pops out immediately. While most of their work is in optics, they have ties across the sciences. There’s an arc of lighter colors across the mid-top, in nanotechnology and biomaterials. The heart of the group has relatively low Rao-Sterling indices of 0.2-0.25. They focus mostly on chemistry, and that research focus is reflected in the map. A lot at the grad students shows that they are in this middle range as well. ANON6, ANON 8 and ANON 10 exceed as well. Though this map is one area where we must be careful not to deceive ourselves. Rao-Sterling scores depend on sampled publications, and these values are relative to the group maximum of 0.735 held by ANON 244 and ANON 255, who were coauthors on a single very interdisciplinary paper. More work on more groups is needed to see what typical scores are. One of the classic studies in the field, Porter et al 2007, suggests a Rao-Stirling score above 0.46 is indicative of truly integrative scholarship.
A next step is to develop a visualization to link scholars in a group to their areas of literature, but for now, this is a quick tour of my research and how it can be used. It’s taken me a couple of year to get to this point, but my code base is now solid enough that I can do groups quickly. This analysis took me an afternoon. I'm working on a journal paper based on this work, and if you have any ideas about how this can be applied to your project, I'm happy to collaborate.