Structural Cohesion: Visualization and Heuristics for Fast Computation with NetworkX and matplotlib

The structural cohesion model is a powerful sociological conception of cohesion in social groups, but its diffusion in empirical literature has been hampered by computational problems. We present useful heuristics for computing structural cohesion that allow a speed-up of one order of magnitude over the algorithms currently available. Both the heuristics and the exact algorithm have been implemented on NetworkX by the first author. Using as examples three large collaboration networks (co-maintenance of Debian packages, co-authorship in Nuclear Theory, and co-authorship in High-Energy Theory) we illustrate our approach to measure structural cohesion in relatively large networks. We also introduce a novel graphical representation of the structural cohesion analysis to quickly spot differences across networks. It is implemented using matplotlib.