Text Mining for the Detection and Categorization of Cyberbullying in Social Media

The goal of this research is to classify the tweets and other social media posts on bullying using a text-mining approach. The study resulted in the development of a method for the detection and categorization of cyberbullying across many media types. This approach integrates textual and metadata data to identify cyberbullying resources within the context of social networks. Finally, cyberbullying samples from the research are classified using a decision tree classifier; once classified, these features are combined with text examples to determine the proposed model's performance. The simulation is conducted to evaluate the classifier's detection performance against state-of-the-art methods. The results show that the proposed method outperforms the current methods in terms of classification and id. Accurateness.