Publication Date: 2023/07/07
Abstract: While online communication can be a great tool for sharing knowledge and opinions, it can also lead to cyberbullying and hatred towards individuals, and the popular Discord platform is no exception. This research aims to create a bot that can prevent cyberbullying incidents in the Discord app. Also, by focusing on the overall security of the bot, the proposed system aims to detect and prevent anomalies and SQL injection attacks. The introduction provides an overview of cyberbullying on Discord and other social media platforms. In the next section, it gives a detailed understanding of past research conducted in the realm of cyberbullying detection on social media using natural language processing techniques and deep learning. The Methodology section focuses on the system architecture and design of text classification models, image classification models, audio classification models, and bot security. The proposed system effectively uses advanced natural language processing techniques and various machine learning classifiers to accurately detect cyberbullying messages in the domains of text, image, and audio on the Discord app.
Keywords: Cyberbullying Detection, Machine Learning Models, Phishing Link Detection, SQL Injection Detection, Content Analysis, Speech-to-Text Conversion, Optical Character Recognition, Event-Driven Programming, Discord Server.
DOI: https://doi.org/10.5281/zenodo.8124230
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23JUN877.pdf
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