Abstract
The opinions and sentiments behind all the posts, comments and statuses shared on social media nowadays can be considered as a useful indicator for many different purposes. These posts reveal how a person perceives things. These sentiments if harnessed strategically can be used to track honest reviews related to various trending products, movies, public figures, events, etc. Twitter is a primary platform for people to share their state of mind in 140 characters or less. Due to the limitation of characters, this data is not structured and well informative. This project experiments to analyze the real-time tweets using text classification algorithm and eventually to display the polarity of the intended topic through charts and scatter plot visualizations. The project helps to harness the huge repository of opinionated data on Twitter and helps in business decisions such as determining a marketing strategy for a new product launch, or predicting ongoing campaign success or defeat.