Maximum Likelihood Estimation on Directed Stochastic Blockmodels for Community Detection in Directed Graphs

The core message of this paper is to formulate directed graph clustering as a maximum likelihood estimation (MLE) problem on the directed stochastic block model (DSBM), and to derive efficient and interpretable clustering algorithms based on this statistical estimation framework.