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Discriminating Power of Centrality Measures by Rombach, M. Puck; Porter, Mason A. is a scholarly article available to read on EtoBox.

What is Discriminating Power of Centrality Measures about?

The calculation of centrality measures is common practice in the study of networks, as they attempt to quantify the importance of individual vertices, edges, or other components. Different centralities attempt to measure importance in different ways. In this paper, we examine a conjecture posed by E. Estrada regarding the ability of several measures to distinguish the vertices of networks. Estrada conjectured that if all vertices of a graph have the same subgraph centrality, then all vertices must also have the same degree, eigenvector, closeness, and betweenness centralities. We provide a counterexample for the latter two centrality measures and propose a revised conjecture.

Author

Rombach, M. Puck; Porter, Mason A.

Published

2013

Language

EN