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What is Eigenvector Centrality Estimates in Networks about?

This document discusses local estimates for eigenvector-like centrality measures in complex networks. It provides a general framework that includes several commonly used centrality measures, such as Bonacich centrality, PageRank centrality, and in-degree vector. The framework defines a spectral centrality vector associated with a weight function on the network. It then shows how this framework can provide local scale estimators and error bounds to approximate global centrality measures in a computationally

Author

Araceli Enríquez Ovando

Language

EN