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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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>> https://lists.nongnu.org/mailman/listinfo/igraph-help
>
>
>
>
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Re: [igraph] community detection significance, Filipe Alberto, 2012/06/15