Seeking "gold standard" to evaluate accuracy of network clustering algorithm I'm currently looking at network clustering algorithms (we're currently looking at both directed and undirected, unweighted networks).  The algorithms we've tried produce visually nice clusters.  However, we would like to evaluate them against some "gold standard" -- a collection of networks in which the clusters have already been identified (and are more-or-less regarded as the clusters by the complex network's research community).


  Question: What are the gold standards for network clustering algorithms?  Where can I access them?
There are a couple of test sets mentioned in Stochastic blockmodels and community structure in networks by Karrer and Newman. One of them is the Karate Club Network, which is rather small, and the other is the Political Blog Network which is bigger. As far as I know, there is no gold-standard for testing clustering algorithms.