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A comparative analysis of link removal strategies in real complex weighted networks

Abstract : In this report we offer the widest comparison of links removal (attack) strategies efficacy in impairing the robustness of six real-world complex weighted networks. We test eleven different link removal strategies by computing their impact on network robustness by means of using three different measures, i.e. the largest connected cluster (LCC), the efficiency (Eff) and the total flow (TF). We find that, in most of cases, the removal strategy based on the binary betweenness centrality of the links is the most efficient to disrupt the LCC. The link removal strategies based on binary-topological network features are less efficient in decreasing the weighted measures of the network robustness (e.g. Eff and TF). Removing highest weight links first is the best strategy to decrease the efficiency (Eff) in most of the networks. Last, we found that the removal of a very small fraction of links connecting higher strength nodes or of highest weight does not affect the LCC but it determines a rapid collapse of the network efficiency Eff and the total flow TF. This last outcome raises the importance of both to adopt weighted measures of network robustness and to focus the analyses on network response to few link removals.
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Contributor : Nelly Lucas <>
Submitted on : Thursday, March 11, 2021 - 2:40:37 PM
Last modification on : Monday, March 15, 2021 - 9:21:50 AM

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M. Bellingeri, D. Bevacqua, F. Scotognella, R. Alfieri, D. Cassi. A comparative analysis of link removal strategies in real complex weighted networks. Scientific Reports, Nature Publishing Group, 2020, 10 (1), ⟨10.1038/s41598-020-60298-7⟩. ⟨hal-03166707⟩



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