All organizations have a ‘deep’ hidden structure based on the social interactions among its members which might or might not coincide with the official formal one. University departments are no exception – if anything, the informal alliances, affinities, and allegiances within academic departments are only too visible and salient.
Network analysis provides one way of visualizing and exploring the ‘deep’ organizational structure. In order to learn how to visualize small networks with R, I collected data on the social interactions within my own department and plugged the dataset in R (igraph package) to get the plot below. The figure shows the social network of my institute based on the co-supervision of student dissertations (each Master thesis has a supervisor who selects a so-called ‘second’ reader who reviews the draft and the two supervisors examine the student during the defence). So each link between nodes (people) is based on one joint supervision of a student. The total number of links (edges) is 264 which covers (approximately) all dissertations defended over the last year. In this version of the graph, the people are represented only by numbers but in the full version the actual names of people are plotted, the links are directional, and additional info (like the grade of the thesis) can be incorporated.
Altogether, the organization appears surprisingly well-integrated. Most ‘outsiders’ and most weakly-connected ‘islands’ are either occasional external readers, or new colleagues being ’socialized’ into the organization. Obviously, some people are more ‘central’ in the sense of connecting to a more diverse set of people, while others serve as boundary-spanners reaching to people who would otherwise remain unconnected to the core. I find the figure intellectually and aesthetically pleasing (given that it is generated with two lines of code) and perhaps a more thorough analysis of the network can be useful in organizational management as well.