[igraph] community detection algorithm and Evaluation

[Fatemeh a]

Hello all,

I am running Community Detection in graphs and I run different community detection algorithm implemented in igraph listed here :

  1. Edge-betweennes.community(w,-d)
  2. walktrap.community (w,-d)
  3. fastgreedy.community(w)
  4. spinglass.community (w,d, not for unconnected graph)
  5. infomap.community (w,d)
  6. label.propagation.community(w) 
  7. Multivel.community(w)
  8.leading.eigenvector.community (w)

as I have two types of graph one is directed an weighted and the other one is undirected and unweighted, the one which I could use for both are four (1,2,4,5) which I get the error on the forth one as my graph is an unconnected graph, so there is three. now I want to compare them using different evaluation metrics provided in here http://lab41.github.io/Circulo/ , as I searched there is modularity and compare.communities ( metrics listed here :http://www.inside-r.org/packages/cran/igraph/docs/compare.communities are ("vi", "nmi","split.join", "rand","adjusted.rand) in igraph.

what I am wondering about are :

• is there any other algorithm which is implemented in igraph and is not in the list? and which will give me overlapping communities as well.
• which of these metric could be used for weighted and directed graph and is there any implementation in igraph?
• also which metric could be used for which algorithm? , as I go through one of the article "edge-betweeness"the metric used in there was the ground truth and they compare to the known community graph.

I would really appreciate if someone could help me.

thank you in advance.

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regards

Fatemeh