In the last decade, the social network has gained remarkable attention. People access social network sites such as Twitter, Facebook LinkedIn, and Google+. People are becoming more interested in and depend on the social network for information, news, and opinion of other users on different subject matters. The heavy dependency on social network sites causes them to generate massive data. The main contribution of this project is the integration of sentimental analysis on location-based Twitter data. Another contribution of this project is the development of a novel user interface, which allows the user to search on a map interactively on Google map. This integrated sentiment analysis works efficiently and performs location-based popularity on persons, products, event or any given topic.