Automated Decision Support System for Cyberbullying Detection
A. Kannammal, Sharma Hitesh Omprakash, J. Danesh Dheerthan · Procedia Computer Science · 2023
Cyberbullying has become a prevalent issue in the digital age, posing serious psychological and emotional risks for individuals, particularly among young people. Detecting and addressing cyberbullying incidents in a timely manner is crucial for ensuring a safe online environment. This project proposes the development of an automated decision support system for cyberbullying detection. The objective of this system is to utilize advanced machine learning and natural language processing techniques to automatically analyse online content, such as text messages, social media posts, and comments, to identify potential instances of cyberbullying. The system will employ a combination of lexical analysis, sentiment analysis, and contextual understanding to accurately detect harmful and offensive language patterns associated with cyberbullying. The proposed system will also incorporate a decision support component to provide actionable insights for intervention and support. It will detect the cyber bullying content in social media before posting so the content will be blocked. When a potential cyberbullying incident is detected, the system will generate alerts and provide information to relevant stakeholders, such as parents, educators, or online platform administrators. This will empower them to take appropriate actions, such as providing counselling, implementing disciplinary measures, or intervening to prevent further harm. To ensure the effectiveness and reliability of the system, a comprehensive dataset of cyberbullying instances will be collected and used for training and testing the machine learning models. Ethical considerations, privacy, and data protection will be carefully addressed throughout the project to safeguard the rights and confidentiality of individuals involved. The success of this project will contribute to the development of an automated solution that complements human efforts in combating cyberbullying. By providing timely detection and decision support, the system aims to foster a safer online environment, protect individuals from cyberbullying incidents, and promote positive digital interactions.