Hi, this is not really straightforward, because most algorithms just want to find dense subgraphs, and although these tend to be small, this is of course not always the case.
Maybe community finding is not exactly what you need. You can take a look at spectral partitioning, if you know the number of communities you want to get. Alternatively, you can try methods that give you a full dendrogram (walktrap or fastgreedy in igraph), and then cut the dendrogram in a way that you don't have big communities. Depending on your data, this might give a lot os isolate vertices, though. Best, Gabor On Tue, Nov 13, 2012 at 2:04 PM, John Jacobson < [email protected]> wrote: > Hello, > > I have a very large weighted, undirected graph that I wish to partition > into communities using the community detection algorithms in the R > package. I was wondering if there is a way to perform community detection > with a constraint on the size of a community. For example, suppose I don't > want any of the communities to have more than 50 vertices. > > Thank You. > > _______________________________________________ > igraph-help mailing list > [email protected] > https://lists.nongnu.org/mailman/listinfo/igraph-help > > -- Gabor Csardi <[email protected]> MTA KFKI RMKI
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