Published Paper Details:

Nowadays almost all the users try to exchange their day to day updates in their life on online social networks like Facebook, Twitter, and a lot more. In general, the users want to tweet on some friend's tweets either in a positive manner or in a negative manner based on their original feelings. In a recent survey report, there are a lot of posts that are contained in shameful tweets with some shameful related comments and replies. These tweets may contain some times information about political, social, and financial life with some shameful related messages, hence there is no method to identify these types of tweets automatically and try to display these tweets separately. Hence in this proposed application, we try to design a new method that can able to identify the tweets and its inner meaning of those tweets and try to categorize the tweets into separate categories like positive, negative, and shameful. Here we try to use Feature Extraction Method along with SVM Classifier algorithm for classifying the shameful tweets and normal tweets individually.