The idea is to use various classification algorithms and sentiment analysis to train on twitter and other social media data to develop a model that detects potential cases of cyberbullying or abuse.A classification model was implemented with experiments and analysis carried out for different features and models with about 73% accuracy using random forest with a maximum depth of 60. The analysis and model is explained in the detection-hate-offensive.pdf file which also serves as the technical paper for this research.
