Discovering overlapping communities using a new diffusion approach based on core expanding and local depth traveling in social networks

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dc.authoridArasteh, Bahman/0000-0001-5202-6315
dc.authoridBouyer, Asgarali/0000-0002-4808-2856;
dc.authorwosidArasteh, Bahman/AAN-9555-2021
dc.authorwosidBouyer, Asgarali/IYS-5116-2023
dc.authorwosidBouyer, Asgarali/JOZ-6483-2023
dc.contributor.authorBouyer, Asgarali
dc.contributor.authorSabavand Monfared, Maryam
dc.contributor.authorNourani, Esmaeil
dc.contributor.authorArasteh, Bahman
dc.date.accessioned2024-05-19T14:46:42Z
dc.date.available2024-05-19T14:46:42Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThis paper proposes a local diffusion-based approach to find overlapping communities in social networks based on label expansion using local depth first search and social influence information of nodes, called the LDLF algorithm. It is vital to start the diffusion process in local depth, traveling from specific core nodes based on their local topological features and strategic position for spreading community labels. Correspondingly, to avoid assigning excessive and unessential labels, the LDLF algorithm prudently removes redundant and less frequent labels for nodes with multiple labels. Finally, the proposed method finalizes the node's label based on the Hub Depressed index. Thanks to requiring only two iterations for label updating, the proposed LDLF algorithm runs in low time complexity while eliminating random behavior and achieving acceptable accuracy in finding overlapping communities for large-scale networks. The experiments on benchmark networks prove the effectiveness of the LDLF method compared to state-of-the-art approaches.en_US
dc.identifier.doi10.1080/03081079.2023.2233050
dc.identifier.endpage1019en_US
dc.identifier.issn0308-1079
dc.identifier.issn1563-5104
dc.identifier.issue8en_US
dc.identifier.scopus2-s2.0-85165326544en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage991en_US
dc.identifier.urihttps://doi.org10.1080/03081079.2023.2233050
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5575
dc.identifier.volume52en_US
dc.identifier.wosWOS:001029698400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal of General Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectSocial Networksen_US
dc.subjectOverlapping Community Detectionen_US
dc.subjectDiffusion Approachen_US
dc.subjectOverlapping Nodeen_US
dc.subjectLocal Depth First Searchen_US
dc.subjectCore Nodeen_US
dc.subject>en_US
dc.titleDiscovering overlapping communities using a new diffusion approach based on core expanding and local depth traveling in social networksen_US
dc.typeArticleen_US

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