Subjectivity analysis of movie reviews using machine learning to perform sentence level classification

Abstract

This research conducts a short review, comparative study and performs sentence level subjectivity analysis using three different machine learning algorithms for movie reviews. Support Vector Machine (SVM) and Naïve Bayes Model have been used for subjective/objective classification using the same data-set (rotten tomato movie reviews) to analyze the result as well as to find the best outcome. Multilayer perceptron (MLP) has been implemented later to the feasibility of it's in differentiating subjective and objective notions. In sentence level classification, using stop words produce a better result than not using stops words. A comparative analysis has also been included to support this claim.