Classification of Sentimental Reviews Using Machine Learning Techniques
Abinash Tripathy, Ankit Agrawal, Santanu Kumar Rath · Procedia Computer Science · 2015
Sentiment Analysis is the most prominent branch of natural language processing. It deals with the text classification in order to determine the intention of the author of the text. The intention can be of admiration (positive) or criticism (Negative) type. This paper presents a comparison of results obtained by applying Naive Bayes (NB) and Support Vector Machine (SVM) classification algorithm. These algorithms are used to classify a sentimental review having either a positive review or negative review. The dataset considered for training and testing of model in this work is labeled based on polarity movie dataset and a comparison with results available in existing literature has been made for critical examination.