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Characterizing the interactions between classical and community-aware centrality measures in complex networks

Abstract : Abstract Identifying vital nodes in networks exhibiting a community structure is a fundamental issue. Indeed, community structure is one of the main properties of real-world networks. Recent works have shown that community-aware centrality measures compare favorably with classical measures agnostic about this ubiquitous property. Nonetheless, there is no clear consensus about how they relate and in which situation it is better to use a classical or a community-aware centrality measure. To this end, in this paper, we perform an extensive investigation to get a better understanding of the relationship between classical and community-aware centrality measures reported in the literature. Experiments use artificial networks with controlled community structure properties and a large sample of real-world networks originating from various domains. Results indicate that the stronger the community structure, the more appropriate the community-aware centrality measures. Furthermore, variations of the degree and community size distribution parameters do not affect the results. Finally, network transitivity and community structure strength are the most significant drivers controlling the interactions between classical and community-aware centrality measures.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-03226733
Contributeur : Stephany Rajeh <>
Soumis le : samedi 15 mai 2021 - 14:28:50
Dernière modification le : dimanche 16 mai 2021 - 03:23:56

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Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi. Characterizing the interactions between classical and community-aware centrality measures in complex networks. Scientific Reports, Nature Publishing Group, 2021, 11 (1), ⟨10.1038/s41598-021-89549-x⟩. ⟨hal-03226733⟩

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