A SENTIMENT ANALYSIS OF AIRLINE SYSTEM USING MACHINE LEARNING ALGORITHMS

Twitter is the popular and commonly used social networking platform because it permits users to express their thoughts, opinions about any item, and allows them to post comments or messages all around the world. Sentiment Analysis techniques are used to study and analyze these reviews or opinions. Sentiment analysis is a NLP technique that is used to express opinions into different sentiments like positive, negative, and neutral. In this paper, we take Airline Dataset from Twitter and did sentiment analysis on that dataset using machine learning algorithms like SVM, Naïve Bayes and Random Forest. Sentiments are expressed in three categories positive, negative and neutral. Our dataset contains 11533 tweets and the dataset is not balanced. The performance of various machine learning algorithms is discussed in this paper.