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Research PapersNo Access

SELF-SIMILARITY IN COMPLEX NETWORKS: FROM THE VIEW OF THE HUB REPULSION

School of Computer and Information Science, Southwest University, Chongqing 400715, China

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School of Computer and Information Science, Southwest University, Chongqing 400715, China

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School of Computer and Information Science, Southwest University, Chongqing 400715, China

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SANKARAN MAHADEVAN

School of Engineering, Vanderbilt University, Nashville, TN 37235, USA

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School of Computer and Information Science, Southwest University, Chongqing 400715, China

School of Engineering, Vanderbilt University, Nashville, TN 37235, USA

Corresponding author.

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https://doi.org/10.1142/S0217984913502011Cited by:20 (Source: Crossref)

Abstract

Complex networks are widely used to model the structure of many complex systems in nature and society. Recently, fractal and self-similarity of complex networks have attracted much attention. It is observed that hub repulsion is the key principle that leads to the fractal structure of networks. Based on the principle of hub repulsion, the metric in complex networks is redefined and a new method to calculate the fractal dimension of complex networks is proposed in this paper. Some real complex networks are investigated and the results are illustrated to show the self-similarity of complex networks.

Keywords:

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Vol. 27, No. 28

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History

Received 30 April 2013

Revised 26 July 2013

Accepted 23 August 2013

Published: 10 October 2013

Keywords