Community detection using NetworkX – Orbifold Consulting
Summary
The ultimate goal in studying networks is to better understand the behavior of the systems they represent. We study the Internet to better understand the flow of data traffic or why communications protocols function the way they do or how we might change the network to make it perform better. The problem of finding groups of nodes in networks is called community detection. Simple though it is to describe, community detection turns out to be a challenging task, but a number of methods have been developed that return good results in practical situations. Let’s look at the largest clique in the karate club: A k-core of a graph G is a maximal connected subgraph of G in which all vertices have degree at least k. Equivalently, it is one of the connected components of the subgraph of G formed by repeatedly deleting all vertices of degree less than k. If a non-empty k-core exists, then, clearly, G has degeneracy at least k, and the degeneracy of G is the largest k for which G has a k-core.