A Fast Community Detection Algorithm Based on Coot Bird Metaheuristic Optimizer in Social Networks

dc.contributor.author Koç, İsmail
dc.date.accessioned 2022-10-08T20:51:32Z
dc.date.available 2022-10-08T20:51:32Z
dc.date.issued 2022
dc.description.abstract Community detection (CD) is critical to understanding complex networks. Researchers have made serious efforts to develop efficient CD algorithms in this sense. Since community detection is an NP-hard problem, utilizing metaheuristic algorithms is preferred instead of classical approaches in solving the problem. For this reason, in this study, six different metaheuristic algorithms called Archimedes optimization algorithm (AOA), Atom search optimization (ASO), Coot Bird Natural Life Model (COOT), Harris Hawks Optimization (HHO), Slime Mould Algorithm (SMA) and Arithmetic Optimization Algorithm (AROA) are used in the solution of CD problems and all of which have been proposed for solving continuous problems in recent years. Since the CD problem has a discrete structure, discrete versions of all the algorithms are produced, and then the proposed discrete algorithms are adapted to the problem. In addition, in the phase of evaluating the objective function of the problem, a fast approach based on CommunityID is proposed to minimize the time cost when solving the problem, and this approach is utilized in all the algorithms when calculating the fitness value. In the experimental studies, firstly, the novel discrete algorithms are compared with each other in terms of solution quality and time and according to these results, COOT becomes the most effective and very fast algorithm. Then, the results obtained by COOT are compared with those of important studies in the literature. When compared in terms of solution quality, it is seen that the COOT algorithm is more effective than the other algorithms. In addition, it is quite obvious that all of the proposed algorithms using the CommunityID-based approach are faster than the other algorithms in the literature in terms of time. As a result, it can be said that COOT can be an effective alternative method for dealing with CD problems. In addition, the approach based on CommunityID can also be utilized in larger networks to obtain remarkable solutions in a much shorter time. en_US
dc.identifier.doi 10.1016/j.engappai.2022.105202
dc.identifier.issn 0952-1976
dc.identifier.issn 1873-6769
dc.identifier.scopus 2-s2.0-85134731638
dc.identifier.uri https://doi.org/10.1016/j.engappai.2022.105202
dc.identifier.uri https://hdl.handle.net/20.500.13091/3094
dc.language.iso en en_US
dc.publisher Pergamon-Elsevier Science Ltd en_US
dc.relation.ispartof Engineering Applications of Artificial Intelligence en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Metaheuristic algorithms en_US
dc.subject Community detection en_US
dc.subject Discrete optimization en_US
dc.subject Graph structures en_US
dc.subject Social networks en_US
dc.subject Modularity en_US
dc.subject Atom Search Optimization en_US
dc.subject Functional Modules en_US
dc.subject Organization en_US
dc.subject Fission en_US
dc.subject Web en_US
dc.title A Fast Community Detection Algorithm Based on Coot Bird Metaheuristic Optimizer in Social Networks en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Koç, İsmail
gdc.author.scopusid 57190306475
gdc.bip.impulseclass C4
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department Fakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümü en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 105202
gdc.description.volume 114 en_US
gdc.description.wosquality Q1
gdc.identifier.openalex W4286484507
gdc.identifier.wos WOS:000838690300002
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gdc.oaire.isgreen false
gdc.oaire.popularity 1.7028729E-8
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gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
gdc.openalex.fwci 11.28184902
gdc.openalex.normalizedpercentile 0.92
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 18
gdc.plumx.mendeley 14
gdc.plumx.scopuscites 23
gdc.scopus.citedcount 23
gdc.virtual.author Koç, İsmail
gdc.wos.citedcount 17
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