Machine learning based twitter data sentiment classification on real time â€˜clean India missionâ€™ tweets - ., sangeeta; Singh Gill, Nasib (International Journal of Engineering and Technology, 2018)
Social networking sites are popular medium to share opinion on various topics. Twitter is one of the social networking site used for tweet posting. Sentiment classification deal with finding the polarity of these tweets as positive, negative or neutral. This analysis can be useful in decision support in different ways. The aim of this paper is to discuss various machine learning algorithm for twitter sentiment classification, compare their results on the basis of Accuracy, Precision, Recall and F-Score. A real time data set for training and testing is created after extraction and cleaning of tweets on â€œClean India Mission or Swachh Bharat Abhiyanâ€. â€œClean India Missionâ€ is a campaign by government of India to clean the country. This paper also compares machine learning algorithms with Bagging, Boosting and Random Forest ensemble approaches.Â