Weighted local clustering coefficient
January 23, 2009 at 12:00 am 1 comment
The generalisation of the local clustering coefficient to weighted networks by Barrat et al. (2004) considers the value of a triplet to be the average of the weights attached to the two ties that make up the triplet. In this post, I suggest three additional methods for defining the triplet value.
The content of this post has been integrated in the tnet manual, see Clustering in Weighted Networks.
Entry filed under: Network thoughts. Tags: clustering coefficient, complex networks, embeddedness, graphs, local, network, social network analysis, valued networks, weighted networks.
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Tore Opsahl 
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David Hope | May 10, 2009 at 12:01 pm
Great to see someone trying to tackle weights in networks – this is very similar to what I’m trying to do for my Ph.D. (over language) I’m just reading your paper ‘Clustering In Weighted Networks’ – very interesting. I actually came up with a (local) weighted clustering coefficient which I use to find cohesion in language: this is simply the sum of the products of the paths and can deal with weighted, ‘unweighted’ (i.e. uniform weights) and both directed and undirected graphs.