Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition

Understand

We study the problem of community detection in multi-layer networks, where pairs of nodes can be related in multiple modalities.

• We introduce a general framework, i.e., mixture multi-layer stochastic block model (MMSBM), which includes many earlier models as special cases.
• We propose a tensor-based algorithm (TWIST) to reveal both global/local memberships of nodes, and memberships of layers.
• We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or the number of layers increases.