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{{Network science}}
The '''stochastic [[Blockmodel|block model]]''' is a [[generative model]] for random [[Graph (discrete mathematics)|graphs]]. This model tends to produce graphs containing ''communities'', subsets of nodes characterized by being connected with one another with particular edge densities. For example, edges may be more common within communities than between communities. Its mathematical formulation has been firstly introduced in 1983 in the field of social network by Holland et al.<ref name="hol" /> The stochastic block model is important in [[statistics]], [[machine learning]], and [[network science]], where it serves as a useful benchmark for the task of recovering [[community structure]] in graph data.
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