A framework for second-order eigenvector centralities and clustering coefficients

DOI10.1098/rspa.2019.0724zbMath1472.65043arXiv1910.12711OpenAlexW2982165638WikidataQ94601096 ScholiaQ94601096MaRDI QIDQ5160897

Francesco Tudisco, Francesca Arrigo, Desmond J. Higham

Publication date: 29 October 2021

Published in: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.12711

zbMATH Keywords

tensorhypergraphcomputational mathematicsstatistical physicsPerron-Frobenius theorylink predictionclustering coefficientapplied mathematicshigher-order network analysis

Mathematics Subject Classification ID

Social networks; opinion dynamics (91D30) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50) Eigenvalues, singular values, and eigenvectors (15A18) Multilinear algebra, tensor calculus (15A69)

Related Items (6)

Ergodicity Coefficients for Higher-Order Stochastic Processes ⋮ Core-Periphery Detection in Hypergraphs ⋮ Nonlinear Perron--Frobenius Theorems for Nonnegative Tensors ⋮ The structure and dynamics of networks with higher order interactions ⋮ Quantifying the structural stability of simplicial homology ⋮ Nonlocal pagerank

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