Version 1
: Received: 28 February 2024 / Approved: 29 February 2024 / Online: 29 February 2024 (11:40:09 CET)
How to cite:
John, J. M.; Bellingeri, M.; Lekha, D. S.; Cassi, D.; Alfieri, R. Robustness of Real-World Networks after Weight Thresholding by Strong Link Removal. Preprints2024, 2024021674. https://doi.org/10.20944/preprints202402.1674.v1
John, J. M.; Bellingeri, M.; Lekha, D. S.; Cassi, D.; Alfieri, R. Robustness of Real-World Networks after Weight Thresholding by Strong Link Removal. Preprints 2024, 2024021674. https://doi.org/10.20944/preprints202402.1674.v1
John, J. M.; Bellingeri, M.; Lekha, D. S.; Cassi, D.; Alfieri, R. Robustness of Real-World Networks after Weight Thresholding by Strong Link Removal. Preprints2024, 2024021674. https://doi.org/10.20944/preprints202402.1674.v1
APA Style
John, J. M., Bellingeri, M., Lekha, D. S., Cassi, D., & Alfieri, R. (2024). Robustness of Real-World Networks after Weight Thresholding by Strong Link Removal. Preprints. https://doi.org/10.20944/preprints202402.1674.v1
Chicago/Turabian Style
John, J. M., Davide Cassi and Roberto Alfieri. 2024 "Robustness of Real-World Networks after Weight Thresholding by Strong Link Removal" Preprints. https://doi.org/10.20944/preprints202402.1674.v1
Abstract
Weight thresholding (WT) is a method intended to decrease the number of links within weighted networks that may otherwise be excessively dense for network science applications. WT aims to remove links to simplify the networks by holding most of the features of the original network. Here, we test the robustness and the efficacy of the node attack strategies on real-world networks subjected to WT that remove links of higher weight (strong links). We measure the network robustness along node removal with the largest connected component (LCC). We find that the real-world networks under study are generally stable in terms of robustness when subjected to WT. Nonetheless, WT by strong link removal changes the efficacy of the attack strategies and the rank of node centralities. Also, WT by strong link removal may trigger a greater change in node centrality rank than WT by removing weak links. Network science research finding important/influential nodes in the network has to consider that simplifying the network with WT methodologies may change the node centrality.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.