[R] Highly Connected Nodes in Igraph
csardi at rmki.kfki.hu
Fri Mar 6 20:27:36 CET 2009
please post to the list instead of posting me directly.
I am sorry to say, but I don't really know what you want to do. First
you asked about highly connected nodes, and now about clustering.
Perhaps you could give an example with the input and the expected
Btw, if you know how to do it with RBGL, then why don't you do it with RBGL?
On Fri, Mar 6, 2009 at 7:45 PM, <surendar.swaminathan at gmail.com> wrote:
> Hello Gabor,
> Thank you for the reply.I used your program to do SNA betweennes,Closenness,Eigen Vector.
> I think I did not put the question properly.What I would like to do is clustering based on Co-authorship network.
> If I have 5 nodes and all the nodes have written one paper & 2,3,4 have written 4 papers together. I want to create cluster based on the node 2,3,4.I have been looking arnd for over a week now.Could not find a way to solve this problem.
> I have 393 such nodes to cluster based on the number of times the authors have published with the other authors.
> Gábor Csárdi-2 wrote:
>> if you have a weighted adjacency matrix, then you don't need graph
>> packages for this, just do
>> rowSums(data != 0)
>> depending you want the sum of the weights of the adjacent edges, or
>> just the number of adjacent edges. Or optionally colSums instead of
>> rowSums if your graph is directed.
>> On Fri, Mar 6, 2009 at 7:00 PM, Sur Nathan
>> <surendar.swaminathan at gmail.com> wrote:
>>> Hello R Help Team,
>>> I have created graph from weighted adjecency matrix .Is there a way I
>>> find highly connected nodes in Igraph like the Package RBGL does.
>>> View this message in context:
>>> Sent from the R help mailing list archive at Nabble.com.
>>> R-help at r-project.org mailing list
>>> PLEASE do read the posting guide
>>> and provide commented, minimal, self-contained, reproducible code.
>> Gabor Csardi <Gabor.Csardi at unil.ch> UNIL DGM
>> R-help at r-project.org mailing list
>> PLEASE do read the posting guide
>> and provide commented, minimal, self-contained, reproducible code.
> Quoted from:
Gabor Csardi <Gabor.Csardi at unil.ch> UNIL DGM
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