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Artificial Intelligence-Driven Cyberbullying Detection: A Survey of Current Techniques | ||
Journal of Information Technology Management | ||
دوره 16، شماره 4، 2024، صفحه 38-63 اصل مقاله (1.82 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22059/jitm.2024.99050 | ||
نویسندگان | ||
Kholood Alfaleh* 1؛ Abdulatif Alabdultif2؛ Suliman Aladhadh1 | ||
1Department of Information Technology, College of Computer Qassim University Buraydah 51452, Saudi Arabia. | ||
2Department of Computer Science, College of Computer, Qassim University, Buraydah 52571, Saudi Arabia. | ||
چکیده | ||
Cyberbullying involves using hurtful or offensive language that goes against basic rules of respect and politeness. It harms the online environment and can negatively affect people by causing harassment, discrimination, or emotional pain. To combat this, it is crucial to develop automated methods for detecting and preventing the dissemination of such content. Deep learning, a branch of artificial intelligence, leverages neural networks to learn from data and perform complex tasks, effectively capturing semantic and grammatical nuances to differentiate between abusive and non-abusive language. This survey paper reviews current techniques and advancements in deep learning-based approaches for detecting cyberbullying content on online platforms, aiming to provide a comprehensive understanding of existing methodologies and identify potential avenues for future research to mitigate the spread and impact of such behaviors on the internet. | ||
کلیدواژهها | ||
Cyberbullying؛ cyber-harassment؛ Deep learning؛ Social Media | ||
مراجع | ||
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