Clustering in complex networks. II. Percolation properties

Abstract

The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the $k$-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.

Updated reference list

References in corpus (2)

• Percolation and Epidemic Thresholds in Clustered Networks
• Clustering in complex networks. I. General formalism

Cited by in corpus (8)

• Critical phenomena in complex networks
• Clustering in complex networks. I. General formalism
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• Percolation in Hierarchical Scale-Free Nets
• Weighted percolation on directed networks
• Transport on weighted Networks: when correlations are independent of degree
• Clusterization, frustration and collectivity in random networks
• Percolation in clustered networks