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arXiv · 1901.09828

A dynamic stochastic blockmodel for interaction lengths

Riccardo Rastelli·Michael Fop
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Abstract

We propose a new dynamic stochastic blockmodel that focuses on the analysis of interaction lengths in networks. The model does not rely on a discretization of the time dimension and may be used to analyze networks that evolve continuously over time. The framework relies on a clustering structure on the nodes, whereby two nodes belonging to the same latent group tend to create interactions and non-interactions of similar lengths. We introduce a fast variational expectation-maximization algorithm to perform inference, and adapt a widely used clustering criterion to perform model choice. Finally, we test our methodology on artificial data, and propose a demonstration on a dataset concerning face-to-face interactions between students in a high-school.

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Riccardo Rastelli, Michael Fop. 2019-01-28. A dynamic stochastic blockmodel for interaction lengths. https://arxiv.org/abs/1901.09828

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