Abstract: Now, social media data is rapidly growing, and it plays an important role in every area from every angle. Researchers are enthusiastic about the social media big data mining area. current web, a range of users use social media and social networks to browse and read people’s connected information. Despite being disgraceful, it has become an important component of social media data. In this paper, I proposed a computerized project for open disgrace identification on Twitter. tweets are classified into five types: Offensive, correlation, condemning, strict/ethnic, joke on personal issues and each post/comment characterized into one of these types. It is seen that out of all the people taking an interest in users who post remarks on a specific occasion, the greater part of them are probably going to embarrass the person in question. Finally, detection of disgracing content using machine learning algorithm and trying to improve detection accuracy.Keywords- Disgracing, online user interaction, public identification, text mining, classification, machine learning, Social Media.