Wmixnet: Software for Clustering the Nodes of Binary and Valued Graphs   using the Stochastic Block Model
  Clustering the nodes of a graph allows the analysis of the topology of a network.   The stochastic block model is a clustering method based on a probabilistic model. Initially developed for binary networks it has recently been extended to valued networks possibly with covariates on the edges.   We present an implementation of a variational EM algorithm. It is written using C++, parallelized, available under a GNU General Public License (version 3), and can select the optimal number of clusters using the ICL criteria. It allows us to analyze networks with ten thousand nodes in a reasonable amount of time. 
Jean-Benoist Leger
stat.CO stat.AP