Day by day, social media and blogs become the best platform to express views and opinions about different issues, such as evaluation of product, services, political matters. The social media becomes micro-blogs, and Twitter becomes one of the most significant sources of information, knowledge and expression of feelings, reactions to the events, to tv-programs, political statements. Nowadays, a lot of factories and big corporations start polls about their new upcoming product to judge and to analyze the reactions of the people and their sentiments about those new products. Now, researchers focus on developing a technology which can identify and detect overall sentiments of users who are present on micro-blogs. Here, in this article, there is a focus on one of the famous social media micro-blog that is “Twitter” and the way of analyzing different models to classify Tweets posted into positive, negative and neutral sentiments. Thus this video shows how to do the Sentiment Analysis of Twitter Data. To do so, they used two classifications models. The first one is a three-way task model for classifying positive, negative and neutral classes sentiments, and second is, a binary task-based model that classify sentiments into two classes that are positive and negative.