Sentiment Analysis of English Tweets Using Rapid Miner

Social networking sites these days are great source of communication for internet users. So these are important source for understanding the emotions of people. In this paper, we use data mining techniques for the purpose of classification to perform sentiment analysis on the views people have shared in Twitter. We collect dataset, i.e. The tweets from twitter that are in natual language and apply text mining techniques -- tokenization, stemming etc to convert them into useful form and then use it for building sentiment classifier that is able to predict happy, sad and neutral sentiments for a particular tweet. Rapid Miner tool is being used, that helps in building the classifier as well as able to apply it to the testing dataset. We are using two different classifiers and also compare their results in order to find which one gives better results.