Lexical sorting centrality to distinguish spreading abilities of nodes in complex networks under the Susceptible-Infectious-Recovered (SIR) model

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dc.authorscopusid57197882972
dc.contributor.authorŞimşek, A.
dc.date.accessioned2021-12-01T18:38:56Z
dc.date.available2021-12-01T18:38:56Z
dc.date.issued2021
dc.department[Belirlenecek]en_US
dc.description.abstractEpidemic modeling in complex networks is a hot research topic in recent years. The spreading of a virus (such as SARS-CoV-2) in a community, spreading computer viruses in communication networks, or spreading gossip on a social network is the subject of epidemic modeling. The Susceptible-Infectious-Recovered (SIR) is one of the most popular epidemic models. One crucial issue in epidemic modeling is the determination of the spreading ability of the nodes. Thus, for example, super spreaders can be detected in the early stages. However, the SIR is a stochastic model, and it needs heavy Monte-Carlo simulations. Hence, the researchers focused on combining several centrality measures to distinguish the spreading capabilities of nodes. In this study, we proposed a new method called Lexical Sorting Centrality (LSC), which combines multiple centrality measures. The LSC uses a sorting mechanism similar to lexical sorting to combine various centrality measures for ranking nodes. We conducted experiments on six datasets using SIR to evaluate the performance of LSC and compared LSC with degree centrality (DC), eigenvector centrality (EC), closeness centrality (CC), betweenness centrality (BC), and Gravitational Centrality (GC). Experimental results show that LSC distinguishes the spreading ability of nodes more accurately, more decisively, and faster. © 2021 The Authoren_US
dc.identifier.doi10.1016/j.jksuci.2021.06.010
dc.identifier.issn13191578
dc.identifier.pmid38620758en_US
dc.identifier.scopus2-s2.0-85110207825en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1016/j.jksuci.2021.06.010
dc.identifier.urihttps://hdl.handle.net/20.500.12684/9920
dc.identifier.wosWOS:000860725300011en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorŞimşek, A.
dc.language.isoenen_US
dc.publisherKing Saud bin Abdulaziz Universityen_US
dc.relation.ispartofJournal of King Saud University - Computer and Information Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCentrality measureen_US
dc.subjectComplex networksen_US
dc.subjectEpidemic modelingen_US
dc.subjectSocial networksen_US
dc.subjectSuper spreaderen_US
dc.subjectSusceptible-Infectious-Recovered modelen_US
dc.titleLexical sorting centrality to distinguish spreading abilities of nodes in complex networks under the Susceptible-Infectious-Recovered (SIR) modelen_US
dc.typeArticleen_US

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