Adapting the Stochastic Block Model to Edge-Weighted Networks
arXiv:1305.5782
Abstract
We generalize the stochastic block model to the important case in which edges are annotated with weights drawn from an exponential family distribution. This generalization introduces several technical difficulties for model estimation, which we solve using a Bayesian approach. We introduce a variational algorithm that efficiently approximates the model's posterior distribution for dense graphs. In specific numerical experiments on edge-weighted networks, this weighted stochastic block model outperforms the common approach of first applying a single threshold to all weights and then applying the classic stochastic block model, which can obscure latent block structure in networks. This model will enable the recovery of latent structure in a broader range of network data than was previously possible.
References in corpus (7)
- Hierarchical structure and the prediction of missing links in networks
- Phase transition in the detection of modules in sparse networks
- An efficient and principled method for detecting communities in networks
- A Bayesian Approach to Network Modularity
- Parsimonious module inference in large networks
- Uncovering latent structure in valued graphs: A variational approach
- Valued Ties Tell Fewer Lies: Why Not To Dichotomize Network Edges With Thresholds
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