Combating Cyber Abuse: A Toxic Comment Detection Model Using Deep Learning

The rapid growth of social media has led to an increase in online toxicity, posing a challenge for maintaining safe and respectful digital spaces. This work aimed to develop an intelligent system for detecting and filtering harmful content using advanced deep learning techniques, including CNN, BiLSTM, and hybrid models. By focusing on languages with complex sentence structures, we will enhance the system's accuracy in detecting toxic comments, ensuring robust performance across diverse content. In addition to traditional classification, we explore proactive moderation tools, such as automated email notifications, to alert users about offensive content, promoting a healthier online environment. This research not only contributes to mitigating online abuse but also provides a framework for creating more inclusive and safer social media platforms. The system's implementation demonstrates the potential of machine learning to address one of the most pressing challenges in digital communication today.