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

Basit Öğe Kaydı
dc.authoridACI, Cigdem/0000-0002-0028-9890
dc.authoridSarac, Esra/0000-0002-2503-0084
dc.authoridYildiz, Eren/0000-0002-4631-7834
dc.contributor.authorCuruk, Eren
dc.contributor.authorAci, Cigdem
dc.contributor.authorEssiz, Esra Sarac
dc.date.accessioned2025-01-06T17:37:19Z
dc.date.available2025-01-06T17:37:19Z
dc.date.issued2018
dc.description3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEG
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 cybcrbullying. A total of 3469 reviews from Youtubc 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 (NIRN(R), 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.
dc.description.sponsorshipBMBB,Istanbul Teknik Univ,Gazi Univ,ATILIM Univ,Int Univ Sarajevo,Kocaeli Univ,TURKiYE BiLiSiM VAKFI
dc.identifier.endpage11
dc.identifier.isbn978-1-5386-7893-0
dc.identifier.startpage6
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2194
dc.identifier.wosWOS:000459847400002
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2018 3rd International Conference on Computer Science and Engineering (Ubmk)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectCyberbullying
dc.subjectClassification
dc.subjectText Minning
dc.subjectMRMR
dc.subjectReliefF
dc.subjectRFE
dc.subjectDVM
dc.subjectRBF
dc.subjectSGD
dc.subjectLogistic Regression
dc.subjectSocial Media
dc.titleThe Effects of Attribute Selection in Artificial Neural Network Based Classifiers on Cyberbullying Detection
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu