In current days there was a lot of abused communication found in social media. A recent survey report confirmed that more than 80 percent of online social networks are having abused or vulgar communication on their user accounts. These types of messages are mainly posted on user walls in order to harass teens, preteens other children by posting these types of offensive messages. Till now no application is providing a solution for this cyber content not to spread on social media, so this motivated me to design this current application for stopping vulgar communication in online social networks. In this proposed application, we mainly try to propose a new representation learning method to tackle this problem for identifying and stopping the abused messages not to communicate in online chat. Here we try to use well-known machine learning algorithms such as Support Vector Machine for classifying the abused messages and normal messages and, we use Porter Stemming Algorithm to pre-process the text messages. This Porter Stemming is a well-known NLT Package, which will divide the whole message into parts and then assign tokens for each individual word. Here, we classify the cyber bullied dialogue into five categories based on literature such as hate, vulgar, offensive, sex and violence.

Cyberbullying, Communication, Natural Language Toolkit, Support Vector Machine, Porter Stemming, Vulgar, Offensive