Cyberbullying is a major problem encountered on internet that affects teenagers and also adults. It has lead to
mishappenings like suicide and depression. Regulation of content on Social media platorms has become a growing need. The
following study uses data from two different forms of cyberbullying, hate speech tweets from Twittter and comments based on
personal attacks from Wikipedia forums to build a model based on detection of Cyberbullying in text data using Natural
Language Processing and Machine learning. Threemethods for Feature extraction and four classifiers are studied to outline the
best approach. For Tweet data the model provides accuracies above 90% and for Wikipedia data it givesaccuracies above 80%.
