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Re: [igraph] random walks with directed edges
From: |
Tamás Nepusz |
Subject: |
Re: [igraph] random walks with directed edges |
Date: |
Wed, 23 May 2012 16:13:18 +0200 |
> the big connected component. Now edge.betweenness.community() reveals
> some meaningful communities. Do you think such an approach is sound?
Well, as long as the communities are meaningful, then I guess this approach is
sound.
> Of course, your suggestion looks really interesting and I will give it
> a try, but I have no knowledge of C++, so I don't know how to manage
> such an analysis... should I use the C++ igraph? or can I call the C++
> code from R in a relatively easy way?
Well, my code compiles to a command line application that takes the network in
an edge list format, tries to fit a stochastic blockmodel to it, and then
returns the classification of nodes into groups (where, say, group 1 = core and
group 2 = periphery) and the connection probabilities within the core, within
the periphery, and between the core and the periphery. So, there's no need for
C++ coding once the code itself is compiled. As for R, you can call the
executable from R using system() and then parse the output to get back the node
classification as an R vector -- but you have to write this glue code yourself.
Best,
T.