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Sentiment Analysis on Product Reviews Using Machine Learning Techniques

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Cognitive Informatics and Soft Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 768))

Abstract

Sentiment Analysis and Opinion Mining is a most popular field to analyze and find out insights from text data from various sources like Facebook, Twitter, and Amazon, etc. It plays a vital role in enabling the businesses to work actively on improving the business strategy and gain an in-depth insight of the buyer’s feedback about their product. It involves computational study of behavior of an individual in terms of his buying interest and then mining his opinions about a company’s business entity. This entity can be visualized as an event, individual, blog post or product experience. In this paper, Dataset has taken from Amazon which contains reviews of Camera, Laptops, Mobile phones, tablets, TVs, video surveillance. After preprocessing we applied machine learning algorithms to classify reviews that are positive or negative. This paper concludes that, Machine Learning Techniques gives best results to classify the Products Reviews. Naïve Bayes got accuracy 98.17% and Support Vector machine got accuracy 93.54% for Camera Reviews.

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Acknowledgements

The author would like to thank to Data Analytics Research Lab, Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad for providing infrastructure to carry my research work. The author acknowledges the Department of Science and Technology (DST), New Delhi, India for granting financial assistance in the form of DST INSPIRE FELLOWSHIP (JRF) during this research work.

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Authors and Affiliations

  1. Department of Computer Science and IT, Dr. Babasaheb Ambedkar Marathwada University, 431004, Aurangabad, Maharashtra, India

    Rajkumar S. Jagdale, Vishal S. Shirsat & Sachin N. Deshmukh

Authors
  1. Rajkumar S. Jagdale
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  2. Vishal S. Shirsat
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  3. Sachin N. Deshmukh
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Corresponding author

Correspondence to Rajkumar S. Jagdale .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Vignana Bharathi Institute of Technology, Hyderabad, Telangana, India

    Pradeep Kumar Mallick

  2. Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Department of Electrical and Electronics Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Rangpo, India

    Akash Kumar Bhoi

  4. Department of Electronic and Computer Engineering, Brunel University London, Uxbridge, Middlesex, United Kingdom

    Ahmed F. Zobaa

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Jagdale, R.S., Shirsat, V.S., Deshmukh, S.N. (2019). Sentiment Analysis on Product Reviews Using Machine Learning Techniques. In: Mallick, P., Balas, V., Bhoi, A., Zobaa, A. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-13-0617-4_61

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