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Social Network Analysis and Mining
Erschienen in: Social Network Analysis and Mining 1/2019

01.12.2019 | Original Article

Immunization of networks with non-overlapping community structure

verfasst von: Zakariya Ghalmane, Mohammed El Hassouni, Hocine Cherifi

Erschienen in: Social Network Analysis and Mining | Ausgabe 1/2019

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Abstract

Although community structure is ubiquitous in complex networks, few works exploit this topological property to control epidemics. In this work, devoted to networks with non-overlapping community structure (i.e., a node belongs to a single community), we propose and investigate three global immunization strategies. In order to characterize the influence of a node, various pieces of information are used such as the number of communities that the node can reach in one hop, the nature of the links (intra-community links, inter-community links), the size of the communities and the interconnection density between communities. Numerical simulations with the susceptible-infected-removed epidemiological model are conducted on both real-world and synthetic networks. Experimental results show that the proposed strategies are more effective than classical alternatives that are agnostic of the community structure. Additionally, they outperform alternative local and global strategies designed for modular networks.
Vorheriger Artikel Localizing and quantifying infrastructure damage using class activation mapping approaches
Nächster Artikel Social BI to understand the debate on vaccines on the Web and social media: unraveling the anti-, free, and pro-vax communities in Italy

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Metadaten
Titel
Immunization of networks with non-overlapping community structure
verfasst von
Zakariya Ghalmane
Mohammed El Hassouni
Hocine Cherifi
Publikationsdatum
01.12.2019
Verlag
Springer Vienna
Erschienen in
Social Network Analysis and Mining / Ausgabe 1/2019
Print ISSN: 1869-5450
Elektronische ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-019-0591-9

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