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 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.

Automated summary

In this study, we investigate the effect of weight thresholding (WT) on the robustness of real-world complex networks. We find that real-world networks subjected to WT hold a robust connectivity structure to node attack even for higher WT values. Weighted node centralities are more stable indicators of node importance in real-world networks subjected to link sparsification compared to binary node centralities.