In this post we build on several of our previous posts to introduce the concepts of Community Structure and Network Modularity. We implement in detail the Girvan-Newman algorithm and apply it to the NIPS co-authorship network.
We hope you enjoy today’s post. We’re looking forward to your comments, feedback and suggestions for follow ups. And of course, don’t forget to:
Network Communities
Empirical networks can display a wide range of structures due, in part due to the underlying process that originated them. In particular, as we already saw in previous posts, networks can have properties multiple components, a non-trivial Degree Distribution, a high Clustering Coefficient, low Network Diameter, a high frequency of specific Network Motifs, etc.
All of these properties contribute to make the network look different from point to point. For example, specific groups of nodes in a network can be significantly denser than others with different dense regions being interconnected by sparsely popu…
