Community detection I
Fast-greedy is a modularity based method - it works by trying to build larger and larger communities by adding vertices to each community one by one and assessing a modularity score at each step. The modularity score is an index of how inter-connected edges are within versus between communities. Thanks to the clustering fast greedy method, we can identify 6 groups, and the modularity index is 0.41.
Community detection II
In contrast, the edge-betweenness is a divisive method - it works by dividing the network into smaller and smaller pieces until it finds edges that it perceives to be ‘bridges’ between communities. With the clustering edge betweenness method, we can identify 18 groups and the modularity index is 0.39.
