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Re: [igraph] community detection significance

From: Moses Boudourides
Subject: Re: [igraph] community detection significance
Date: Thu, 14 Jun 2012 22:00:48 +0300

What exactly is "community significance"? Any literature? --Moses

On Thu, Jun 14, 2012 at 9:58 PM, Tamás Nepusz <address@hidden> wrote:
> Dear Filipe,
> None of the community significance algorithms are implemented in igraph yet 
> and I am not aware of any such implementations yet. A relatively simple 
> approach is to take each vertex in the community, calculate their internal 
> and external degrees (i.e. the number of edges incident on them that lead 
> inside the community and outside the community, respectively), and then run a 
> Mann-Whitney U-test. The null hypothesis is that the distribution of internal 
> and external degrees is the same (in other words, the community is not a real 
> one because it is just as dense "inside" as "outside"), and the test will 
> reject it if the community is a significant one. I'm sure that there are far 
> better methods than this, but this is relatively easy to implement both in R 
> and in Python using igraph.
> Best,--
> T.
> On Thursday, 14 June 2012 at 20:55, Filipe Alberto wrote:
>> Dear list,
>> I have been using igraph to detect communities in networks. However, I would 
>> like to use some method to get significance of the derived communities. I 
>> see that there are several algorithms published, but I don't know if they 
>> are available in igraph or if some of the users have implemented them using 
>> R and igraph?
>> Thanks you for your help,
>> All the best,
>> Filipe Alberto
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