Detecting Twitter Cyberbullying Using Machine Learning with Big Data

Abstract

Online media is a stage where numerous youthful individuals are getting tormented. As person to person communication destinations are expanding, cyberbullying is expanding step by step. To recognize word likenesses in the tweets made by menaces and utilize AI and can build up a ML model naturally recognize online media tormenting activities. In any case, numerous online media tommenting identification methods have been actualized, however numerous of them were printed based. The objective of this paper is to show the execution of programming that will distinguish tormented tweets, posts, and so on An AI model is proposed to distinguish and forestall tormenting on Twitter. Two classifiers for example SVM and RF are utilized for preparing and testing the online media tormenting content. Both SVM (Support Vector Machine) and RF had the option to recognize the genuine positives with 71.25% and 52.70% precision individually. Yet, SVM beats RF of comparable work on the equivalent dataset.