[Top][All Lists]

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

[igraph] clustering coefficient in bipartite network

From: Simone Gabbriellini
Subject: [igraph] clustering coefficient in bipartite network
Date: Thu, 25 Nov 2010 17:22:35 +0100

Hello List,

I am trying to reproduce the clustering measures detailed in Latapy et al. 
Social Networks, 30 (2008).

I attempted successfully to reproduce the ccN(G) clustering, which is basically 
an extension for bipartite networks of the global transitivity measure.

I am stuck with the cc. measure of clustering coefficient, an extension of 
local transitivity for bipartite network - a reprise of what Borgatti and 
Everett have already suggested in 1997. 

I have to find, for each distance-2 neighbors of a node (which are still nodes 
of the same set), how many nodes of the other set they have in common. 

This is not all of what is needed to implement this measure, but it would be a 
great step for me...

In order to find distance-2 neighbors for each node, I can use a partition, as 
Tamas suggested in a previous thread.

V(g)[type==FALSE]$neibi<-neighborhood(bipartite.projection(g)[[1]], 1)

V(g)[type==TRUE]$neibi<-neighborhood(bipartite.projection(g)[[2]], 1)

While in order to find neighbors in the bipartite, I can simply use:

V(g)$nei<-neighborhood(g, 1)

now, how can I confront a node with every nodes listed in its neibi attribute 
in order to find if there are duplicates in each nei attributes? this is the 
hardest part I cannot solve.

any help more than welcome!

thanks in advance,

reply via email to

[Prev in Thread] Current Thread [Next in Thread]