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I am looking for implementations of community detection algorithms, such as the Girvan-Newman algorithm (2002). I have visited the websites of several researchers in this field (Newman, Santo, etc.) but was unable to find any code. I imagine someone out there published implementations of these algorithms (maybe even a toolkit?), but I can't seem to find it.
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M. Girvan and M. E. J. Newman have proposed one of the most widely adopted community detection algorithms, the Girvan-Newman algorithm. According to them, groups of nodes in a network are tightly connected within communities and loosely connected between communities.
Girvan-Newman Algorithm for Community Detection. Under the Girvan-Newman algorithm, the communities in a graph are discovered by iteratively removing the edges of the graph, based on the edge betweenness centrality value. The edge with the highest edge betweenness is removed first.
Community detection, also called graph partition, helps us to reveal the hidden relations among the nodes in the network. Many algorithms have been developed to detect communities (Clauset et al., 2004; Girvan and Newman, 2002; Lancichinetti and Fortunato, 2009).
Community Detection Techniques. Community detection methods can be broadly categorized into two types; Agglomerative Methods and Divisive Methods. In Agglomerative methods, edges are added one by one to a graph which only contains nodes. Edges are added from the stronger edge to the weaker edge.
Community detection algorithms are sometimes part of a library (such as JUNG for java) or a tool (see Gephi). When authors publish a new method, they do sometimes make their code available. For example, the Louvain and Infomap methods.
Side note: Girvan-Newman algorithm is sometimes still used, but it has mostly been replaced by faster and more accurate methods. For a good overview of the topic, I recommend Community detection algorithms: a comparative analysis or the longer Community detection in graphs (103 pages).
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