Group adjacency matrices: Effective visualisation of community structure in large networks

Community identification in large networks is one of the most popular Social Network Analysis applications, and many algorithms have been proposed. The visualisation of the identified structure remains a problem in large networks. The traditional graph-based visualisation does not scale well with many communities and their numerous relations among each other. In this paper, we propose a visualisation based on abstracted adjacency matrices, which scales much better, since there are no overlaps in the two-dimensional matrix. We also propose a couple of enhancements and tweaks to get the best possible user experience with this approach.