Norah Alsunaidi, Sarah Aljbali, Y. Yasin, Hamoud Aljamaan
{"title":"Arabic Cyberbullying Detection Using Machine Learning: State of the Art Survey","authors":"Norah Alsunaidi, Sarah Aljbali, Y. Yasin, Hamoud Aljamaan","doi":"10.1145/3593434.3593968","DOIUrl":null,"url":null,"abstract":"Cyberbullying (CB) is a global dilemma that is growing rapidly to affect more individuals including minors. The devastating consequences of CB indicate a pressing necessity to regulate unethical or illegal users' online behaviors. A remarkable number of researchers attempted to harness the potential of machine learning to detect and prevent such harmful behaviors, however, the existing studies targeting Arabic-based content are still emerging. Therefore, this paper provides a comprehensive review of the published empirical studies in CB detection in Arabic-based content with an emphasis on the adapted methodologies, gaps, and challenges. We hope this work would support researchers in the area of CB-detection to foster a safe online environment and protect against any harmful consequences of CB among users.","PeriodicalId":178596,"journal":{"name":"Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3593434.3593968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Cyberbullying (CB) is a global dilemma that is growing rapidly to affect more individuals including minors. The devastating consequences of CB indicate a pressing necessity to regulate unethical or illegal users' online behaviors. A remarkable number of researchers attempted to harness the potential of machine learning to detect and prevent such harmful behaviors, however, the existing studies targeting Arabic-based content are still emerging. Therefore, this paper provides a comprehensive review of the published empirical studies in CB detection in Arabic-based content with an emphasis on the adapted methodologies, gaps, and challenges. We hope this work would support researchers in the area of CB-detection to foster a safe online environment and protect against any harmful consequences of CB among users.