A new fast entropy-based method to generate composite centrality measures in complex networks

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dc.contributor.authorSabah, Levent
dc.contributor.authorŞimşek, Mehmet
dc.date.accessioned2023-07-26T11:59:03Z
dc.date.available2023-07-26T11:59:03Z
dc.date.issued2023
dc.departmentDÜ, Rektörlük, Bilgi İşlem Daire Başkanlığıen_US
dc.description.abstractDetermining the centrality of nodes in complex networks provides practical benefits in many areas such as detecting influencer nodes, viral marketing, and preventing the spread of rumors. On the other hand, there is no consensus for the definition of centrality. Therefore, different centrality measures such as degree, closeness, and betweenness have been developed to measure the centrality of a node. However, each centrality measure highlights the various characteristics of the nodes in the network from its own point of view. This causes each centrality measure to rank the nodes in a different order. In recent years, researchers have focused on approaches that combine multiple centrality measures. Thus, the perspectives of different centrality measures can be considered simultaneously. In this study, we have proposed a fast and efficient method using the analytic hierarchy process and entropy weighting to combine multiple centrality measures. We tested the proposed method with synthetic and real datasets and compared the results with those of state-of-the-art methods. The experimental results showed the proposed method to be competitive with these advanced methods, whereas it performed much better than the other methods in terms of computational speed. This indicated that our proposed method could be applied to large and dynamic complex networks.en_US
dc.identifier.doi10.1002/cpe.7657
dc.identifier.issn1532-0626
dc.identifier.issn1532-0634
dc.identifier.scopus2-s2.0-85147996971en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.urihttps://doi.org/10.1002/cpe.7657
dc.identifier.urihttps://hdl.handle.net/20.500.12684/13626
dc.identifier.wosWOS:000931198800001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorSabah, Levent
dc.institutionauthorŞimşek, Mehmet
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofConcurrency and Computation-Practice & Experienceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectAnalytic Hierarchy Process; Centrality Measures; Complex Networks; Entropy Weightingen_US
dc.subjectIdentifying Influential Spreaders; Nodes; Ranking; Weight; Poweren_US
dc.titleA new fast entropy-based method to generate composite centrality measures in complex networksen_US
dc.typeArticleen_US

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