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All Journal TechComp Innovations: Journal of Computer Science and Technology
Hossain, Md. Safaet
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Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management

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AI-Powered Frameworks for the Detection and Prevention of Cyberbullying Across Social Media Ecosystems Mondol, Md. Anas; Uddaula, Md. Ashaf; Hossain, Md. Safaet; Siddika, Mst. Ayesha
TechComp Innovations: Journal of Computer Science and Technology Vol. 2 No. 1 (2025): TechComp Innovations: Journal of Computer Science and Technology
Publisher : Pusat Riset dan Inovasi Nasional Mabadi Iqtishad Al Islami

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70063/techcompinnovations.v2i1.59

Abstract

This study presents an advanced AI-powered framework to detect and prevent cyberbullying across diverse social media platforms using a multiclass classification approach. Addressing the growing complexity and linguistic diversity of online abuse, the research integrates various machine learning (RF, LR, SVM) and deep learning (Bi-LSTM, BERT) models trained on a balanced dataset covering bullying categories based on religion, age, ethnicity, gender, and neutral content. Data preprocessing, tokenization, feature extraction via TF-IDF and CountVectorizer, and class balancing using SMOTE were applied to enhance model accuracy. The proposed system further supports real-time detection through social media APIs, offering dynamic monitoring and intervention capabilities. Among the tested models, Random Forest and BERT achieved the highest classification performance with 94% accuracy. Despite its robust architecture, limitations include dependence on English-language datasets, exclusion of multimodal data (e.g., memes, audio), and API restrictions that challenge scalability. Future development will focus on incorporating vision-language models and optimizing the system for real-time, multilingual, and multimodal environments. This study contributes to digital safety efforts by proposing a scalable and adaptive detection system suitable for safeguarding users from evolving forms of online harassment.
Co-Authors Mondol, Md. Anas Siddika, Mst. Ayesha Uddaula, Md. Ashaf