Opinion Mining Classification using Naive Bayes Algorithm
Raghavendra Vijay Bhasker Vangara1, Kailashnathan Thirupathur2, Shiva Prasad Vangara3

1Raghavendra Vijay Bhasker Vangara*, Department of Mathematics and Computer Science, University of Missouri-St. Louis, Missouri, USA.
2Kailashnathan Thirupathur, Department of Computer Science, University of Bridgeport, Connecticut, USA.
3Shiva Prasad Vangara, Department of Information Systems, Indiana Tech University, Indianapolis, USA.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 19, 2020. | Manuscript published on March 10, 2020. | PP: 495-498 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2402039520/2020©BEIESP | DOI: 10.35940/ijitee.E2402.039520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: With the recent advancement in the field of online services, the importance of a review for a product has also gone up. In this paper we focus on the aspect of reducing the time and effort for the user by recommending the best product to him. For this to be achieved, this paper proposes a Naive Bayes Classifier which labels the reviews accurately and combines the reviews to give a final rating to the product. The amazon product review data consisting of both negative and positive reviews was used for training and testing purposes. The model’s performance is evaluated, and results are analysed.
Keywords: Natural Language Processing, Sentiment Analysis, Opinion Mining, Machine Learning.
Scope of the Article: Machine Learning.