Sentiment Analysis on e-commerce product reviews using Machine Learning and Natural Language Processing

Authors

  • Prof. Pradeep N. Fale Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.
  • Nikita Swain UG Student, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.
  • Pranay Rahangdale UG Student, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.
  • Pranay Waghmare UG Student, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.
  • Harshwardhan Bagde UG Student, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.
  • Nikhil Dhakate UG Student, Department of Information Technology, Priyadarshini College of Engineering, Nagpur, India.

Keywords:

NLP Natural Language Processing, sentiments, product reviews, machine learning

Abstract

Reputation-predicated trust models are widely utilized in e-commerce applications, and feedback ratings are aggregated to compute sellers’ reputation trust scores. The “all good reputation” quandary however is prevalent in current reputation systems – reputation scores are ecumenically high for sellers and it is difficult for potential buyers to cull trustworthy sellers. Predicated on the optical discernment that buyers often express opinions openly in free text feedback comments, we have proposed CommTrust, a multi-dimensional trust evaluation model, for computing comprehensive trust problems for sellers in e-commerce applications. Different from subsisting multidimensional trust models, we compute dimension trust scores and dimension weights automatically via extracting dimension ratings from feedback comments using Natural Language Processing (NLP).

References

Afsal Ali, Jisha P Abraham, Surekha Mariyam Varghese, "A Multi-Dimensional Trust Model and Fuzzy Decision System for ECommerce", International Journal for Scientific Research & Development, Sp. Issue - Data Mining 2015.

Suraj Gund, Akash Gaykwad, Akshada Patil, Payal Nikam, Pankaj Agarkar, "Novel Approach for Mining E-Commerce Feedback Comments using COMM Trust Data Mining Algorithm", International Journal for Scientific Research & Development, Vol. 4, Issue 03, 2016.

Xiuzhen Zhang, Lishan Cui, and Yan Wang, "Computing Multidimensional Trust by Mining E-Commerce Feedback Comments'', Journal of LAtex class files, vol. 6, no. 1, January 2017. [4] M. A. Shafin, M. M. Hasan, M. R. Alam, M. A. Mithu, A. U. Nur and M. O. Faruk, "Product Review Sentiment Analysis by Using NLP and Machine Learning in Bangla Language," 2020 23rd International Conference on Computer and Information Technology (ICCIT), 2020, pp. 1-5, doi: 10.1109/ICCIT51783.2020.9392733. [5] D.Mali, M. Abhyankar, P. Bhavarthi, K. Gaidhar, M. Bangare, "Sentiment Analysis of product reviews for e-commerce recommendation", International Journal of Management and Applied Science, ISSN: 2394-7926 Volume-2, Issue-1, Jan.-2016 [6] Aswini U and Akila Devi T.R, "CommTrust: Computing Multi-Dimensional Trust by Mining E-Commerce Feedback Comments", International Journal of Emerging Technology in Computer Science & Electronics (IJETCSE) ISSN: 0976-1353 Volume 22 Issue 2 – MAY 2016.

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Published

18-04-2022

How to Cite

Prof. Pradeep N. Fale, Nikita Swain, Pranay Rahangdale, Pranay Waghmare, Harshwardhan Bagde, & Nikhil Dhakate. (2022). Sentiment Analysis on e-commerce product reviews using Machine Learning and Natural Language Processing. International Journal for Research Publication and Seminar, 13(3), 31–35. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/521

Issue

Vol. 13 No. 3 (2022): Volume 13 | Issue 3 | 2022 (NSCIT)

Section

Original Research Article

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