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Exploring Classification Techniques for Sentiment Analysis
Mahesh G.1, Satish Kumar T.2, Shreya S.3, Sushmitha N.4, Sripad T.5

1Dr. Mahesh G.*, Department of Computer Science and Engineering, B M S Institute of Technology and Management, Bangalore, India.
2Dr. Satish Kumar T., Department of Computer Science and Engineering, B M S Institute of Technology and Management, Bangalore, India.
3Ms. Shreya S., Department of Department of Computer Science and Engineering, B M S Institute of Technology and Management, Bangalore, India.
4Ms. Sushmitha N., Department of Computer Science and Engineering, B M S Institute of Technology and Management, Bangalore, India.
5Mr. Sripad T., Department of Computer Science and Engineering, B M S Institute of Technology and Management, Bangalore, India.
Manuscript received on February 02, 2020. | Revised Manuscript received on February 10, 2020. | Manuscript published on March 30, 2020. | PP: 720-724 | Volume-8 Issue-6, March 2020. | Retrieval Number: E6897018520/2020©BEIESP | DOI: 10.35940/ijrte.E6897.038620

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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: In the recent years, there has been tremendous improvements in the Information Technology industry. Every day 2.5 quintillion bytes of data is generated, this provides sentiment analysis to become a key tool to make something out of it. This has allowed companies to grab this key acumen and automate the needed processes. This information can serve as good source for extracting useful insights regarding the products/services. It would be helpful for the product owners if these thousands of reviews could be summarized using the latest technologies. Also it would be more useful if the sentiment scores are provided for each aspects of products/services. This paper presents Sentiment Analysis for various predefined aspects for Hotel Reviews. We have used Naive Bayes Classifier for classifying hotel reviews as positive or negative and we have evaluated the performance and suggested few future enhancements.
Keywords: Sentiment Analysis, Opinion Mining, Naive Bayes.
Scope of the Article: Data mining.