International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 191

India | Computer Science Engineering | Volume 5 Issue 4, April 2016 | Pages: 819 - 821


Sentiment Classification using Machine Learning Techniques

Suchita V Wawre, Sachin N Deshmukh

Abstract: Large amount of information are available online on web. The discussion forum, review sites, blogs are some of the opinion rich resources where review or posted articles is their sentiment, or overall opinion towards the subject matter. The opinions obtained from those can be classified in to positive or negative which can be used by customer to make product choice and by businessmen for finding customer satisfaction. This paper studies online movie reviews using sentiment analysis approaches. In this study, sentiment classification techniques were applied to movie reviews. Specifically, we compared two supervised machine learning approaches SVM, Navie Bayes for Sentiment Classification of Reviews. Results states that Nave Bayes approach outperformed the svm. If the training dataset had a large number of reviews, Naive bayes approach reached high accuracies as compare to other.

Keywords: Sentimental Analysis, supervised Algorithm, Naive bayes, Support vector machine



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