Projects per year
Abstract
Communities in multi-layer networks consist of nodes with similar connectivity patterns across all layers. This article proposes a tensor-based community detection method in multi-layer networks, which leverages available node-wise covariates to improve community detection accuracy. This is motivated by the network homophily principle, which suggests that nodes with similar covariates tend to reside in the same community. To take advantage of the node-wise covariates, the proposed method augments the multi-layer network with an additional layer constructed from the node similarity matrix with proper scaling, and conducts a Tucker decomposition of the augmented multi-layer network, yielding the spectral embedding vector of each node for community detection. Asymptotic consistencies of the proposed method in terms of community detection are established, which are also supported by numerical experiments on various synthetic networks and two real-life multi-layer networks.
Original language | English |
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Pages (from-to) | 915–926 |
Number of pages | 12 |
Journal | Journal of Business & Economic Statistics |
Volume | 41 |
Issue number | 3 |
Online published | 5 Jul 2022 |
DOIs | |
Publication status | Published - 2023 |
Funding
This research is supported in part by HK RGC grants GRF-11300919, GRF-11304520, and GRF-11301521.
Research Keywords
- Community detection
- multi-layer network
- network homophily
- stochastic block mode
- tensor decomposition
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Dive into the research topics of 'Covariate-assisted community detection in multi-layer networks'. Together they form a unique fingerprint.Projects
- 3 Finished
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GRF: Joint Modeling of Hypergraph Networks for Community Detection and Graph Embedding
WANG, J. (Principal Investigator / Project Coordinator)
1/01/22 → 1/08/22
Project: Research
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GRF: Hierarchical Modeling of Directed Acyclic Graphs: Estimation, Selection and Asymptotics
WANG, J. (Principal Investigator / Project Coordinator)
1/01/21 → 1/08/22
Project: Research
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GRF: Latent Factor Modeling of Large-Scale Directed Networks with Covariates and Structures
WANG, J. (Principal Investigator / Project Coordinator)
1/01/20 → 1/08/22
Project: Research