is there a way to set the resolution parameter when using the function cluster_louvain to detect communities in igraph for R? It makes a lot of difference for the result, as this parameter is related to the hierarchical dissimilarity between nodes. Thank you.
The easiest way to do it is through the resolution
package, available in this link https://github.com/analyxcompany/resolution
It is based on this paper http://arxiv.org/pdf/0812.1770.pdf
It pretty much has 2 functions cluster_resolution()
and cluster_resolution_RandomOrderFULL()
.
In both you can state the resolution t
and how many repetitions you want rep
. And, you can just use the igraph object in the function.
cluster_resolution_RandomOrderFULL(g,t=0.5)
cluster_resolution_RandomOrderFULL(g,rep=20)
NOTE/EDIT: it will not accept signed networks though! I'm trying to either contact the owner of the code or costumize it myself to make it suitable for signed networks.
EDIT2: I was able to translate the function community_louvain.m from the Brain Connectivity Toolbox for Matlab to R.
Here is the github link for the signed_louvain()
you can pretty much just put for ex. signed_louvain(g, gamma = 1, mod = 'modularity')
it works with igraph or matrix objects as input. If it has negative values, you have to choose mod = 'neg_sym'
or 'neg_asym'
.
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