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Artificial Intelligence-Driven Cyberbullying Detection: A Survey of Current Techniques

عنوان مقاله: Artificial Intelligence-Driven Cyberbullying Detection: A Survey of Current Techniques
شناسه ملی مقاله: JR_JITM-16-4_003
منتشر شده در در سال 1403
مشخصات نویسندگان مقاله:

Alafleh - Department of Information Technology, College of Computer Qassim University Buraydah ۵۱۴۵۲, Saudi Arabia.
Alabdultif - Department of Computer Science, College of Computer, Qassim University, Buraydah ۵۲۵۷۱, Saudi Arabia.
Aladhadh - Department of Information Technology, College of Computer Qassim University Buraydah ۵۱۴۵۲, Saudi Arabia.

خلاصه مقاله:
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.

کلمات کلیدی:
Cyberbullying, cyber-harassment, Deep learning, Social media

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/2111631/