4

So I am working on a new project looking at formal and informal networks between businesses in the same industry. Namely, I am looking at joint ventures, fractional acquisitions, minority share ownership, and board of director relationships between companies. I want to see if I can identify the occurrences of "weak ties" (Granovetter, 1973), meaning ties between densely interconnected clusters. However, I was not sure if software was available to do that type of cluster and then weak tie identification? I am pretty familiar with the ERGM models and the Statnet packages, but I have not seen an functionality for this in those packages. I might be able to use a latent space model (Handcock, 2006) to identify clusters and then eyeball the weak ties, but that seemed a bit arbitrary--though I might have to resort to that. Does anyone know of any better software packages or code for cluster/community detection and then the identification of weak ties?

krishnab
  • 1,008
  • 7
  • 12

1 Answers1

1

A logical candidate is edge centrality, in igraph:

edge.betweenness.estimate(graph, e=E(graph), directed = TRUE, cutoff, weights = NULL)
micans
  • 1,689
  • 8
  • 11
  • Oh that is brilliant. I had not considered edge.betweenness, but it makes total sense. Thanks micans. – krishnab Sep 08 '12 at 05:25