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[igraph] Community detection based on conductance

From: Tim Althoff
Subject: [igraph] Community detection based on conductance
Date: Mon, 5 May 2014 10:06:38 -0700


I am performing community detection on citation network graphs (~20k nodes). It seems like all (most?) community detection algorithms are based on modularity which according to this paper (http://dl.acm.org/citation.cfm?id=2350193) is a bad idea. They propose conductance (or e.g. triangle participation ratio) as a metric to optimize for communities. In particular I am interested in a score for maximum community saliency (or e.g. minimum conductance cut).

Does iGraph have such capabilities? I could find anything about conductance in the docs.

I believe the Stanford SNAP library has similar functionality  (C++) but I would prefer staying with Python if possible.

Any comments and ideas are very welcome!


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