Sentiment analysis on twitter feeds

In this paper we examine sentiment analysis on Twitter data. We are using polarity feature to examine the polarity between [-5,5] and second is frequency feature to examine how many times the word is repeating. This analysis utilises the naive Bayes Classifier to classify Tweets into positive, negative or neutral sets. Further classification is in to extremely negative and extremely positive sets. We present experimental evaluation of our dataset and classification results. A case study is presented to illustrate the use and effectiveness of the proposed system.