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.
Original language | English |
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Title of host publication | Proceedings of EASE 2023 - Evaluation and Assessment in Software Engineering |
Publisher | Association for Computing Machinery |
Pages | 499-504 |
Number of pages | 6 |
ISBN (Electronic) | 9798400700446 |
DOIs | |
State | Published - 14 Jun 2023 |
Event | 27th International Conference on Evaluation and Assessment in Software Engineering, EASE 2023 - Oulu, Finland Duration: 14 Jun 2023 → 16 Jun 2023 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 27th International Conference on Evaluation and Assessment in Software Engineering, EASE 2023 |
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Country/Territory | Finland |
City | Oulu |
Period | 14/06/23 → 16/06/23 |
Bibliographical note
Publisher Copyright:© 2023 ACM.
Keywords
- Arabic Cyberbullying
- Classification
- Cyberbullying Detection
- Machine Learning
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software