Sentiment Analysis on Nepali Movie Reviews using Machine Learning
This research article presents machine learning methods for detecting the sentiment expressed by movie reviews. The semantic orientation of a review can be positive or negative. Analysis of opinion for particular product, news or document could be beneficial to many companies, institutions and individuals for marketing, advertising, question answering, product selection and so on. We have created a Nepali movie review dataset with total 500 samples having 250 samples per each positive and negative class of sentiment from various online sources. Sentiment analysis system implements various natural language processing techniques for document preprocessing and feature extraction. Naive Bayes based machine learning technique is used for the classification of the sentiment. Empirical results shows, classification accuracies are, 79.23% of precision, 78.57% of recall and 78.90% of F score.