PMID: 22587143May 17, 2012Paper

Removing spurious interactions in complex networks

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
An Zeng, Giulio Cimini

Abstract

Identifying and removing spurious links in complex networks is meaningful for many real applications and is crucial for improving the reliability of network data, which, in turn, can lead to a better understanding of the highly interconnected nature of various social, biological, and communication systems. In this paper, we study the features of different simple spurious link elimination methods, revealing that they may lead to the distortion of networks' structural and dynamical properties. Accordingly, we propose a hybrid method that combines similarity-based index and edge-betweenness centrality. We show that our method can effectively eliminate the spurious interactions while leaving the network connected and preserving the network's functionalities.

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Citations

Mar 29, 2014·PLoS Computational Biology·Florian KlimmPeter J Mucha
May 14, 2014·PloS One·Hao LiaoYi-Cheng Zhang
Mar 11, 2016·Scientific Reports·Liming PanChin-Kun Hu
Jun 19, 2015·Scientific Reports·Hao Liao, An Zeng
Oct 18, 2014·Scientific Reports·Liyang YaoZengru Di
Aug 17, 2018·Journal of the Royal Society, Interface·Lovro Šubelj
Oct 30, 2016·PloS One·An Zeng, Stefano Battiston
Sep 1, 2019·Scientific Reports·Zeynab Samei, Mahdi Jalili
Jul 4, 2019·Chaos·Ke-Ke ShangYan Wang
Sep 26, 2012·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·An Zeng, Weiping Liu

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