Abstract
Abstract: Cyber bullying is a major problem encountered on internet that affects teenagers and also adults. It has led to mishappenings like suicide and depression. Regulation of content on Social media platforms has become a growing need. The following study uses data from two different forms of cyber bullying, hate speech tweets from Twittter and comments based on personal attacks from Wikipedia forums to build a model based on detection of cyber bullying in text data using Natural Language Processing and Machine learning. Three methods 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 gives accuracies above 80
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