Effect of Weight Thresholding on the Robustness of Real-World Complex Networks to Central Node Attacks
In this study, we investigate the effect of weight thresholding (WT) on the robustness of real-world complex networks. Here, we assess the robustness of networks after WT against various node attack strategies. We perform WT by removing a fixed fraction of weak links. The size of the largest connect...
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Veröffentlicht in: | Mathematics (Basel) 2023-08, Vol.11 (16), p.3482 |
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Sprache: | eng |
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Zusammenfassung: | In this study, we investigate the effect of weight thresholding (WT) on the robustness of real-world complex networks. Here, we assess the robustness of networks after WT against various node attack strategies. We perform WT by removing a fixed fraction of weak links. The size of the largest connected component indicates the network’s robustness. We find that real-world networks subjected to WT hold a robust connectivity structure to node attack even for higher WT values. In addition, we analyze the change in the top 30% of central nodes with WT and find a positive correlation in the ranking of central nodes for weighted node centralities. Differently, binary node centralities show a lower correlation when networks are subjected to WT. This result indicates that weighted node centralities are more stable indicators of node importance in real-world networks subjected to link sparsification. |
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ISSN: | 2227-7390 2227-7390 |
DOI: | 10.3390/math11163482 |