Combined centrality measures for an improved characterization of influence spread in social networks

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dc.contributor.authorSimsek, Mehmet
dc.contributor.authorMeyerhenke, Henning
dc.date.accessioned2021-12-01T18:48:15Z
dc.date.available2021-12-01T18:48:15Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractInfluence Maximization (IM) aims at finding the most influential users in a social network, that is, users who maximize the spread of an opinion within a certain propagation model. Previous work investigated the correlation between influence spread and nodal centrality measures to bypass more expensive IM simulations. The results were promising but incomplete, since these studies investigated the performance (i.e. the ability to identify influential users) of centrality measures only in restricted settings, for example, in undirected/unweighted networks and/or within a propagation model less common for IM. In this article, we first show that good results within the Susceptible-Infected-Removed propagation model for unweighted and undirected networks do not necessarily transfer to directed or weighted networks under the popular Independent Cascade (IC) propagation model. Then, we identify a set of centrality measures with good performance for weighted and directed networks within the IC model. Our main contribution is a new way to combine the centrality measures in a closed formula to yield even better results. Additionally, we also extend gravitational centrality (GC) with the proposed combined centrality measures. Our experiments on 50 real-world data sets show that our proposed centrality measures outperform well-known centrality measures and the state-of-the art GC measure significantly.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [1059B191700869]; German Research Foundation (DFG)German Research Foundation (DFG) [ME 3619/3-2]en_US
dc.description.sponsorshipThe Scientific and Technological Research Council of Turkey (TUBITAK) (Project number: 1059B191700869); and German Research Foundation (DFG) within Priority Programme 1736 (Grant: ME 3619/3-2).en_US
dc.identifier.doi10.1093/comnet/cnz048
dc.identifier.issn2051-1310
dc.identifier.issn2051-1329
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85081970204en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1093/comnet/cnz048
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10490
dc.identifier.volume8en_US
dc.identifier.wosWOS:000519568400021en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherOxford Univ Pressen_US
dc.relation.ispartofJournal Of Complex Networksen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectsocial networksen_US
dc.subjectinfluence maximizationen_US
dc.subjectcentrality measuresen_US
dc.subjectIC propagation modelen_US
dc.subjectinfluential spreadersen_US
dc.subjectInfluence Maximizationen_US
dc.subjectDynamicsen_US
dc.subjectUsersen_US
dc.titleCombined centrality measures for an improved characterization of influence spread in social networksen_US
dc.typeArticleen_US

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