What question did this study set out to answer?

To develop a Hierarchical Stochastic Block Model that generalizes the Stochastic Block Model for replicated networks and simplifies model selection.

The hierarchical stochastic block model for replicated networks

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To develop a Hierarchical Stochastic Block Model that generalizes the Stochastic Block Model for replicated networks and simplifies model selection.
Introduced a Hierarchical Pitman-Yor prior for block allocation in replicated networks.
Developed a novel MCMC algorithm for posterior inference.
Applied the model to co-authorship and brain connectomic networks.
Successfully modeled replicated networks with shared latent blocks.
Avoided the need for predefined block numbers in each graph.
Demonstrated improved vertex clustering and community detection capabilities.

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Randomized trial demonstrates a novel model for network data in various fields, suggesting improved analysis.

Battiston et al. (2026) studied this question.

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