Sparse networks with core-periphery structure

Journal article

We propose a statistical model for graphs with a core-periphery structure. We give a precise notion of what it means for a graph to have this structure, based on the sparsity properties of the subgraphs of core and periphery nodes. We present a class of sparse graphs with such properties, and provide methods to simulate from this class, and to perform posterior inference. We demonstrate that our model can detect core-periphery structure in simulated and real-world networks.

Authors: Naik, C; Caron, F; Rousseau, J

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Institute of Mathematical Statistics
• Journal: Electronic Journal of Statistics
• Volume: 15
• Issue: 1
• Pages: 1814-1868
• Publication date: 2021-01-01
• DOI: 10.1214/21-ejs1819
• ISSN: 1935-7524
• Language: English
• Keywords: point processes; Bayesian nonparametrics; networks; FFR; random graphs; Poisson random measures; sparsity; completely random measures