We introduce a Bayesian estimator of the underlying class structure in the stochastic block model, when the number of classes is known. The estimator is the posterior mode corresponding to a Dirichlet prior on the class proportions, a generalized Bernoulli prior on the class labels, and a beta prior on the edge probabilities. We show that this estimator is strongly consistent when the expected degree is at least of order , where is the number of nodes in the network.
"Bayesian Community Detection." Bayesian Anal. 13 (3) 767 - 796, September 2018. https://doi.org/10.1214/17-BA1078