Sentiment Analysis for Bullying Word Detection in Social Network

As a side effect of increasingly popular social media, cyberbullying has emerged as a serious problem afflicting children, adolescents and young adults. Machine learning techniques make automatic detection of bullying messages in social media possible, and this could help to construct a healthy and safe social media environment. In this meaningful research area, one critical issue is robust and discriminative numerical representation learning of text messages. In this paper, we propose a new representation learning method to tackle this problem. Our method named natural language processing and artificial intelligence. Sentiment analysis is one of the method which classify the given sentence as positive, neutral and negative. natural language processing which classifies the data using navy bayies classifier. We use the social media tweeter to find the bullying words and classify the words or text as positive, neutral and negative.