الفهرس 
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Abstract
With the rise of digital communication platforms, cyberbullying has become a pressing issue, affecting individuals worldwide. The Arabic-speaking community is no exception, as online harassment and abusive behavior have become prevalent. Cyberbullying detection is the main key to control racism and hate speech over the internet especially on social media. Detection of cyberbullying in Arabic is challenging due to the variety of expressions and different Arabic dialects. Detecting and combating cyberbullying in Arabic poses unique challenges due to the complexity of the language. To develop robust NLP models for cyberbullying detection, the availability of annotated corpora is crucial. These corpora should include a diverse range of Arabic text samples, encompassing different forms of cyberbullying, including offensive language, threats, and personal attacks. Collaborative efforts involving researchers, linguists, and online platforms are necessary to build comprehensive and representative datasets that reflect the Arabic cyberbullying landscape. However, Natural Language Processing (NLP) techniques provide a promising avenue to tackle this problem effectively. Many researches discussed this topic using only 1 dialect and achieved great results. In our research, we consolidated datasets with multiple Arabic dialects from different social media platforms. Text pre- processing enhanced the performance of the used models. We classified the dataset using classical machine learning model, deep learning model and ChatGPT. The experiments showed a significant performance for the multi-dialect comments. Thus, it will be useful for effectively monitoring the Arabic content on the internet.
Detecting cyberbullying in Arabic using NLP techniques is an ongoing research area with several challenges. Some of the key challenges include the scarcity of labeled datasets, the diversity of Arabic dialects, the need for language-specific tools and resources, and the dynamic nature of online communication. Overcoming these challenges requires collaborative efforts between researchers, language experts, and technology companies to develop robust and culturally sensitive NLP models.
Cyberbullying is a serious concern in the Arabic-speaking world, and addressing it requires the application of advanced NLP techniques. By adapting and developing language-specific models, preprocessing techniques, and annotated corpora, we can make significant progress in detecting and mitigating cyberbullying in Arabic. Ultimately, fostering a safe online environment for Arabic speakers relies on continued research, collaboration, and the responsible deployment of NLP technologies.