Abstract
Social media is one of the most influential tool for sharing information across different regions among different users .The people sharing their interests in various aspects in online social networking platforms like Facebook, twitter etc. Therefore the usage of hate text steadily increasing. Nowadays it has been reviled unfair behavior of the users in social networking sites. The existence of abusive text on different online social networking platforms and identification of such text is a big challenging task. To understand the complexity of language constructs in different languages is very difficult .Already lot of research work has completed in English language. This paper gives detail analysis of detecting hate text in various languages Hindi, urdu, Arabic, Bengali, Telugu. We incorporated various kinds of ML and DL based algorithms to identify hate text in OSN’s. A review is done related to different classifiers where a comparison made between different models of ML, DL algorithms. Finally finds the accurate method to classify the text is offensive or not by finding the parameters i.e. accuracy and F1score
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