Sparse networks with core-periphery structure
Copyright policy )Sparse networks with core-periphery structure
We propose a statistical model for graphs with a core-periphery structure. To do this we define 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.
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Primary: 62F15, 05C80. Secondary: 60G55, Bayesian inference, sparsity, Random graphs (graph-theoretic aspects), FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Bayesian nonparametrics, Methodology (stat.ME), completely random measures, networks, Density (toughness, etc.), Point processes (e.g., Poisson, Cox, Hawkes processes), Poisson random measures, random graphs, point processes, Statistics - Methodology
Social and Information Networks (cs.SI), FOS: Computer and information sciences, Physics - Physics and Society, Primary: 62F15, 05C80. Secondary: 60G55, Bayesian inference, sparsity, Random graphs (graph-theoretic aspects), FOS: Physical sciences, Computer Science - Social and Information Networks, Physics and Society (physics.soc-ph), Bayesian nonparametrics, Methodology (stat.ME), completely random measures, networks, Density (toughness, etc.), Point processes (e.g., Poisson, Cox, Hawkes processes), Poisson random measures, random graphs, point processes, Statistics - Methodology
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