A Centrality Ranking Strategy in Modular Complex Networks
Résumé
The traditional descending order ranking scheme of centrality measures is agnostic of the mesoscopic organization of most real-world networks. To address this issue, we propose a community-aware ranking scheme. It selects the top central nodes in each community and ranks them in decreasing order of their community size. Then it moves to the next most central node in each community and proceeds with the same ordering strategy. This approach consistently outperforms the classical descending order ranking scheme, as shown in experiments with the Susceptible-Infected-Recovered (SIR) diffusion model on a set of synthetic and real-world networks using various centrality measures. It paves the way for increased performance in multiple applications such as viral marketing, awareness campaigns, hindering misinformation, and vaccination strategies in networks with community structure.
Domaines
Informatique [cs]Origine | Fichiers produits par l'(les) auteur(s) |
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