Haifa Saleh Alfurayj (KSA)

Haifa’s project aims to enhance cyberbullying detection by exploring the causative factor of cyberbullying spreading, known as Bystander Contagion. This often-overlooked aspect plays a crucial role in the escalation of cyberbullying behavior. Haifa plans to investigate the detection of cyberbullying through the evaluation of users’ profiles, activities, and social media history, with a specific focus on bystander contagion. The goal is to identify influential cyberbullies or bystanders, enabling the suspension of their accounts to effectively reduce cyberbullying incidents.

In developing the cyberbullying detection model, Haifa will address key points, including the influence and characteristics of bystanders, measurement of bystanders’ contagiousness in cyberbullying diffusion, and identification of the most influential users capable of influencing others. The project will utilize datasets from the Twitter platform, with a focus on Arabic language tweets, acknowledging the unique challenges posed by the complex nature of cyberbullying in Arabic. Haifa’s methodology involves labeling and annotating the data, preprocessing procedures, and applying natural language processing, sentiment analysis, and machine learning with feature extraction for classification purposes.