There have been rapid developments in model-based clustering of graphs, also known as
block modelling, over the last ten years or so. We review different approaches and …

The stochastic block model (SBM) is a mixture model for the clustering of nodes in networks.
The SBM has now been employed for more than a decade to analyze very different types of …

An efficient MCMC algorithm is presented to cluster the nodes of a network such that nodes
with similar role in the network are clustered together. This is known as block-modeling or …

Significant progress has been made recently on theoretical analysis of estimators for the
stochastic block model (SBM). In this paper, we consider the multi-graph SBM, which serves …

A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is
proposed. The probability model assumes that the vertices of the digraph are partitioned into …

Modelling relationships between individuals is a classical question in social sciences and
clustering individuals according to the observed patterns of interactions allows us to uncover …

Stochastic blockmodels and variants thereof are among the most widely used approaches to
community detection for social networks and relational data. A stochastic blockmodel …

Finding communities in complex networks is a challenging task and one promising
approach is the Stochastic Block Model (SBM). But the influences from various fields led to a …

The community structure that is observed in empirical networks has been of particular
interest in the statistics literature, with a strong emphasis on the study of block models. We …

This chapter describes the basic variants of the stochastic blockmodel (SBM), and a
consistent Bayesian formulation that allows readers to infer them from data. The focus is on …