Hello everyone,
I am finding ways of divide my network into modules and I saw that the package
in python comes with several alternatives. I wanted to implement the Modularity
(Q) as defined by Newman on 2006 on PNAS
(http://www.pnas.org/content/103/23/8577.full
<http://www.pnas.org/content/103/23/8577.full>) and I saw that you use have
implemented several other formulations of modularity. It seems that the same
formula shown on PNAS was used in the “community_leading_eigenvector” method,
that is based on https://arxiv.org/pdf/physics/0605087.pdf.
<https://arxiv.org/pdf/physics/0605087.pdf.It> Is this correct?
Also, for large sparse matrices, would you rather recommend this method or the
“community_fastgreedy” optimization?
Thanks a lot for your help!
Cheers,
Daniele
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