Aprahamian, Mary and Higham, Desmond J. and Higham, Nicholas J. (2015) Matching Exponential-Based and Resolvent-Based Centrality Measures. [MIMS Preprint]
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Abstract
The relative importance of nodes in a network can be quantified via functions of the adjacency matrix. Two popular choices of function are the exponential, which is parameter-free, and the resolvent function, which yields the Katz centrality measure. Katz centrality can be the more computationally efficient, especially for large directed networks, and has the benefit of generalizing naturally to time-dependent network sequences, but it depends on a parameter. We give a prescription for selecting the Katz parameter based on the objective of matching the centralities of the exponential counterpart. For our new choice of parameter the resolvent can be very ill conditioned, but we argue that the centralities computed in floating point arithmetic can nevertheless reliably be used for ranking. Experiments on \revised{six} real networks show that the new choice of Katz parameter leads to rankings of nodes that \revised{generally} match those from the exponential centralities well in practice.
Item Type: | MIMS Preprint |
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Additional Information: | To appear in Journal of Complex Networks |
Uncontrolled Keywords: | Katz centrality; Katz parameter; adjacency matrix; matrix exponential; matrix resolvent; network analysis; inverse iteration; condition number |
Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 05 Combinatorics MSC 2010, the AMS's Mathematics Subject Classification > 15 Linear and multilinear algebra; matrix theory MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis |
Depositing User: | Nick Higham |
Date Deposited: | 20 May 2015 |
Last Modified: | 20 Oct 2017 14:13 |
URI: | https://eprints.maths.manchester.ac.uk/id/eprint/2298 |
Available Versions of this Item
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Matching Exponential-Based and Resolvent-Based Centrality Measures. (deposited 07 Jan 2015)
- Matching Exponential-Based and Resolvent-Based Centrality Measures. (deposited 20 May 2015) [Currently Displayed]
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