Volume 2 - Issue 2, March - April 2026

The widespread use of the internet has made social media a primary medium for communication. Along with its benefits, the increase in online interactions has also led to a rise in cyberbullying, which can cause serious psychological and physical harm, especially to women and children. This project focuses on designing an effective machine learning model to identify cyberbullying content on social media platforms. The system uses a labelled text dataset obtained from Kaggle, categorized as normal or cyberbullying. After data collection, preprocessing steps such as cleaning, normalization, and feature reduction are performed. A decision tree algorithm is then trained to classify the text data, and its performance is evaluated using test samples. The proposed model accurately distinguishes harmful content, enabling early detection and contributing to a safer online environment.

Mohammed Aashiq S, Dr.Gobi I,"Detection of Cyberbullying on Social Media Using Machine Learning" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(736-740) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.