# Finding “weak ties” in network data

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?

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edge.betweenness.estimate(graph, e=E(graph), directed = TRUE, cutoff, weights = NULL)