A Separable Model for Dynamic Networks

Details A Separable Model for Dynamic Networks A Separable Model for Dynamic Networks

2010-11-08

arxiv.org/abs/1011.1937v1

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26 pages (including a 4-page appendix)

Scientific paper

Models of dynamic networks - networks that evolve over time - have manifold applications. We develop a discrete-time generative model for social network evolution that inherits the richness and flexibility of the class of exponential-family random graph models. The model facilitates separable modeling of the tie duration distributions and the structural dynamics of tie formation. We develop likelihood-based inference for the model, and provide computational algorithms for maximum likelihood estimation. We illustrate the interpretability of the model in analyzing a longitudinal network of friendship ties within a school.

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