Published Paper Details:

Children are increasingly becoming vulnerable to cyber harassment and predatory behavior on social media. Hence, this project aims to enhance the online safety of children by building a system which uses machine learning algorithms to detect and combat online harassment. The developed system integrates various supervised learning algorithms namely, support vector machine, random forest, naive bayes, k nearest neighbors and decision tree. Upon analyzing user content, the algorithm seeks possible abuse potential regarding posts and messages. Numerous harassing and non-harassing texts are included in the dataset which is used to create algorithms for prediction of such actions in real time. The system will first send alerts to a designated authority within the cyber cell every time, austere patterns are observed. This way, no time is wasted in the intervention. The system further enables providing a quicker and reasonable approach to tackle the issues that come up with young people by ensuring their safety as much as possible.