The Effects of Attribute Selection in Artificial Neural Network Based Classifiers on Cyberbullying Detection

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dc.contributor.authorCuruk, Eren
dc.contributor.authorAci, Cigdem
dc.contributor.authorSarac Essiz, Esra
dc.date.accessioned2025-01-06T17:29:48Z
dc.date.available2025-01-06T17:29:48Z
dc.date.issued2018
dc.description3rd International Conference on Computer Science and Engineering, UBMK 2018 -- 20 September 2018 through 23 September 2018 -- Sarajevo -- 143560
dc.description.abstractRecently, as a result of the rapid increase of information communication technologies, the use of smartphones, tablets and laptop computers has become widespread. Especially among young people, social networks have become a part of everyday life and the cyberbullying problem has arisen as a result of hiding the credentials of people in cyberspace and reaching every level. In this study was carried out assays for the detection of cyberbullying. A total of 3469 reviews from Youtube were tagged as positive and negative, depending on whether have contained bullying. In the analyzes, the number of features of the data set was reduced to 10, 50, 100, 250 and 500 using the minimum redundancy and maximum relevance (MRMR), ReliefF and recursive feature elimination (RFE) algorithms as feature selection algorithms, support vector machines (SVM), stochastic gradient descent (SGD), radial basis function (RBF) and logistic regression (LR) have been preferred as classification algorithms. As a result of the experimental studies, the use of the SGD classifier together with the RFE attribute selection algorithm resulted 0.943 F-measure value. Other quality selection algorithms did not produce as high values as RFE, but F-measure values of about 0.76 to 0.84 were obtained. © 2018 IEEE.
dc.identifier.doi10.1109/UBMK.2018.8566312
dc.identifier.endpage11
dc.identifier.isbn978-153867893-0
dc.identifier.scopus2-s2.0-85060584100
dc.identifier.startpage6
dc.identifier.urihttps://doi.org/10.1109/UBMK.2018.8566312
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1363
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofUBMK 2018 - 3rd International Conference on Computer Science and Engineering
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectClassification
dc.subjectCyberbullying
dc.subjectDVM
dc.subjectLogistic Regression
dc.subjectMRMR
dc.subjectRBF
dc.subjectReliefF
dc.subjectRFE
dc.subjectSGD
dc.subjectSocial Media
dc.subjectText Minning
dc.titleThe Effects of Attribute Selection in Artificial Neural Network Based Classifiers on Cyberbullying Detection
dc.typeConference Object

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