Troll Detection Using Artificial Intelligence and Machine Learning
As the usage of social media platforms increased, trolling and use of abusive language has burgeoned exponentially. A major reason for this is that there is no surveillance on most of these platforms. Anyone can fall prey to trolling, regardless of their age. This paper focuses on using Artificial Intelligence and Machine learning algorithms to invigilate such bullies and further classify them for enhanced analysis. We will be creating and using several preprocessing functions, semantic analyzers and classification algorithms for this project. The output of these analyzers will be then fed to algorithms such as Naive Bayes and classifiers like Decision Tree, Random forest, Multinomial, Logistic regression to segregate the trolls in different categories like offensive, targeted, individual, group etc and use visual representation tools to improve the analysis.
Keywords - Social Media; Offensive; Trolling; Bullying; Abusive; Artificial Intelligence.