Detection and Cross-domain Evaluation of Cyberbullying in Facebook Activity Contents for Turkish

dc.authoridInan, Ali/0000-0002-3149-1565
dc.authoridOzel, Selma Ayse/0000-0001-9201-6349
dc.contributor.authorCoban, Onder
dc.contributor.authorOzel, Selma Ayse
dc.contributor.authorInan, Ali
dc.date.accessioned2025-01-06T17:37:48Z
dc.date.available2025-01-06T17:37:48Z
dc.date.issued2023
dc.description.abstractCyberbullying refers to bullying and harassment of defenseless or vulnerable people such as children, teenagers, and women through any means of communication (e.g., e-mail, text messages, wall posts, tweets) over any online medium (e.g., social media, blogs, online games, virtual reality environments). The effect of cyberbullying may be severe and irreversible and it has become one of the major problems of cyber-societies in today's electronic world. Prevention of cyberbullying activities as well as the development of timely response mechanisms require automated and accurate detection of cyberbullying acts. This study focuses on the problem of cyberbullying detection over Facebook activity content written in Turkish. Through extensive experiments with the various machine and deep learning algorithms, the best estimator for the task is chosen and then employed for both cross-domain evaluation and profiling of cyber-aggressive users. The results obtained with fivefold cross-validation are evaluated with an average-macro F1 score. These results show that BERT is the best estimator with an average macro F1 of 0.928, and employing it on various datasets collected from different OSN domains produces highly satisfying results. This article also reports detailed profiling of cyber-aggressive users by providing even more information than what is visible to the naked eye.
dc.identifier.doi10.1145/3580393
dc.identifier.issn2375-4699
dc.identifier.issn2375-4702
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85160200464
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1145/3580393
dc.identifier.urihttps://hdl.handle.net/20.500.14669/2371
dc.identifier.volume22
dc.identifier.wosWOS:000998929700022
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAssoc Computing Machinery
dc.relation.ispartofAcm Transactions on Asian and Low-Resource Language Information Processing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectFacebook
dc.subjectcyber-aggression
dc.subjectcyberbullying
dc.subjectonline social networks
dc.subjectmachine learning
dc.titleDetection and Cross-domain Evaluation of Cyberbullying in Facebook Activity Contents for Turkish
dc.typeArticle

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