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Title: Node assortativity in complex networks: An alternative approach
Authors: Thedchanamoorthy, G
Piraveenan, M
Kasthuriratna, D
Senanayake, U
Keywords: Node assortativity
complex networks
alternative approach
Issue Date: 1-Jan-2014
Publisher: Elsevier
Series/Report no.: Procedia Computer Science;Vol 29 Pages 2449-2461
Abstract: Assortativity quantifies the tendency of nodes being connected to similar nodes in a complex network. Degree Assortativity can be quantified as a Pearson correlation. However, it is insufficient to explain assortative or disassortative tendencies of individual nodes or links, which may be contrary to the overall tendency of the network. A number of ‘local’ assortativity measures have been proposed to address this. In this paper we define and analyse an alternative formulation for node assortativity, primarily for undirected networks. The alternative approach is justified by some inherent shortcomings of existing local measures of assortativity. Using this approach, we show that most real world scale-free networks have disassortative hubs, though we can synthesise model networks which have assortative hubs. Highlighting the relationship between assortativity of the hubs and network robustness, we show that real world networks do display assortative hubs in some instances, particularly when high robustness to targeted attacks is a necessity.
ISSN: 1877-0509
Appears in Collections:Research Papers - SLIIT Staff Publications

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