This paper mainly focuses on the classification of the tweets based on the emotion in which they prompt. The proposed method will extract the tweets on any particular issue and will assist us to analyze the opinion of the people. The tweets can be classified as positive negative or neutral against the particular issue in which the query was made to extract the tweets. The technology which we use is the twitter API, which will assist us in extracting the tweets relevant the particular issue. The next step is to process the tweets i.e. here we will remove all unwanted images, punctuations and special characters. And at last all the tweets will be converted into lowercase for further steps. The classification of final processed tweets will employ a supervised classification method. The basic classifier used in this method is Naive Bayes classifier to classify the emotion of the tweets. The algorithm is trained by all the possible extent. Finally the percentage of the positive and negative tweets will be calculated. Based on the graphical representation we can create a new strategy for the particular issue.

Tweets, Supervised Classification,Positive and Negative tweet

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