Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks

Abstract

Current Bayesian models for dynamic social network data have focused on modelling the influence of evolving unobserved structure on observed social interactions. However, an understanding of how observed social relationships from the past affect future unobserved structure in the network has been neglected. In this paper, we introduce a new probabilistic… (More)
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