Thanks for your replies! As far as I know snappy doesn't have this capability although it part of the SNAP C++ code base. That might be my best bet (unless somebody else has implemented conductance in igraph already).
Thanks! On Tue, May 6, 2014 at 2:11 PM, Gábor Csárdi <[email protected]> wrote: > On Mon, May 5, 2014 at 1:06 PM, Tim Althoff <[email protected]> wrote: > >> Hi, >> >> 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! >> > > How about this: http://snap.stanford.edu/snappy/ ? > > G. > > >> >> Thanks, >> Tim >> >> _______________________________________________ >> igraph-help mailing list >> [email protected] >> https://lists.nongnu.org/mailman/listinfo/igraph-help >> >> > > _______________________________________________ > igraph-help mailing list > [email protected] > https://lists.nongnu.org/mailman/listinfo/igraph-help > >
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