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Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Mar;85(3 Pt 2):036101. Epub 2012 Mar 5.

Removing spurious interactions in complex networks.

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Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700 Fribourg, Switzerland.


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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