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Re: [igraph] Re: [statnet_help] Re: gplot.layout with valued edges


From: Alexander
Subject: Re: [igraph] Re: [statnet_help] Re: gplot.layout with valued edges
Date: Tue, 17 Mar 2009 10:50:19 -0400

Hi,

thanks for the suggestion about the new version. I installed it and
I'm now trying to replicate some Fowler's results to test it.

I have another question:

I want to examine the fact that the nodes in my network are divided
into two groups based on an attibute. This is why I was using the
brokerage measure of the sna package. However, I want a measure that
takes into account the weight of the edges. So can I use closeness()
but with the within / between group distinction in some way?

looking at the r interface there does not seem to be a way to define
the 'to' vertex set, but could I do this if I create two new weight
attributes - one for within-group and one for between group, and then
used those as weights?

Again, thanks

Alexander

On 3/17/09, Jose Quesada <address@hidden> wrote:
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> Hash: SHA1
>
> Gábor Csárdi wrote:
>> Alexander,
>>
>> On Tue, Mar 17, 2009 at 1:07 AM, Alexander Jerneck
>> <address@hidden> wrote: [...]
>>> Newman's measure of betweeness centrality for scientific
>>> collaborations [1]
>>
>> The (not yet finished) 0.6 version of igraph has weighted
>> betweenness, I think this is the same as the measure in Newman's
>> paper. You just need to calculate the weights of the edges and call
>> betweenness().
>>
>> You can download an R source package from here:
>> http://cneurocvs.rmki.kfki.hu/igraph/download/igraph_0.6.tar.gz and
>> an R package for windows from here:
>> http://cneurocvs.rmki.kfki.hu/igraph/download/igraph_0.6.zip
>>
>>> Fowler's adaptation of this measure to directed networks (of
>>> cosponsorship in the US Congress) [2]
>>
>> Version 0.6 also has weighted closeness, and this looks the same to
>> me as Fowler's measure of 'connectedness'. Again, just calculate
>> the weights, and then call closeness().
>>
>> Best, Gabor
>>
>> [...]
>>
> Just a quick note, the windows package there is pretty old, and
> there's one typo on graph.incidence().
> It will return:
> Error in graph.incidence.dense(indicende, directed = directed, mode =
> mode,  :
>   object "weigted" not found
>
> This has been fixed in more recent 0.6 versions.
>
> Best
> - -Jose
>
> - --
> Jose Quesada, PhD.
> Max Planck Institute,
> Center for Adaptive Behavior and cognition,
> Berlin
> http://www.josequesada.name/
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