Microblogging today has become a very popular communication tool in recent times. Millions of users share opinions on different aspects of life everyday in popular social networking sites such as Twitter, Tumblr and Facebook. Impressed by its growth, companies and media organisation are increasingly seeking ways to mine these social media for information about what people think about their companies and products. In this work, a hybrid method which performs the classification of tweet sentiment in Twitter has been executed. In this work, different methods for enhancing the accuracy of a Naive Bayes classifier for sentiment analysis has been explored and implemented. There is also a feature to compare two related trends in the twitter world which could be used to analyse the better product or better opinion in the region or worldwide.
