A Nonlinear Spectral Method for Core--Periphery Detection in Networks
DOI10.1137/18M1183558zbMath1499.05402arXiv1804.09820OpenAlexW2962743802WikidataQ128076491 ScholiaQ128076491MaRDI QIDQ5025758
Francesco Tudisco, Desmond J. Higham
Publication date: 3 February 2022
Published in: SIAM Journal on Mathematics of Data Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1804.09820
networksspectral methodnonlinear eigenvaluescore-peripherymesoscale structurenonlinear Perron-Frobenius
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Social networks; opinion dynamics (91D30) Deterministic network models in operations research (90B10) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50) Edge subsets with special properties (factorization, matching, partitioning, covering and packing, etc.) (05C70)
Related Items (13)
Uses Software
Cites Work
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- A nodal domain theorem and a higher-order Cheeger inequality for the graph \(p\)-Laplacian
- Navigability of interconnected networks under random failures
- The university of Florida sparse matrix collection
- Network Properties Revealed through Matrix Functions
- Node and Layer Eigenvector Centralities for Multiplex Networks
- Community Detection in Networks via Nonlinear Modularity Eigenvectors
- Network partition via a bound of the spectral radius
- The Perron--Frobenius Theorem for Multihomogeneous Mappings
- The contractivity of cone-preserving multilinear mappings
- Core-Periphery Structure in Networks (Revisited)
- Core-Periphery Structure in Networks
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