> are these good indicators that maybe the network has a core-periphery > structure, with nested k-groups, instead of connected communities with > some links between them?
Yes, I strongly suspect so. > again, if this is a suitable answer, is there any core-periphery > algorithm in igraph? Well, as a first approximation, you can say that nodes with a low coreness value are the periphery and the rest is the core. Alternatively, you could say that the big strongly connected component is the core and the rest is the periphery. You could also try to fit a stochastic blockmodel to the network with two groups -- this is not implemented in igraph, but I have a working implementation for both traditional and degree-corrected stochastic blockmodel fitting in C++ (using igraph) so I can help you with that. The source code is here in case you are interested: https://github.com/ntamas/blockmodel This paper gives you a short overview about the existing methods in Section 2.1 and also proposes a new method: http://www.amath.unc.edu/Faculty/mucha/Reprints/coreperiphery.pdf Best, T. _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
