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Review Article
Analyzing Customer Review Sentiments using Machine Learning
Omness Eliel Samuel Amari1
Arun Udayasuriyan2
1 Department of Information Technology & Computer Science, Parul University, Gujarat, India. 2 Assistant Professor, Department of MCA, Faculty of IT & CS, Parul University, Gujarat, India.
Published Online: January-February 2026
Pages: 76-80
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260701009
References
1. Sudhir & al. Comparative study of various approaches, applications and classifiers for sentiment analysis. Prajval Sudhir, Varun
Deshakulkarni Suresh, et al., Global Transitions Proceedings, Vol. 2, Issue 2, pp. 205–211, 2021. Available on Comparative study of
various approaches, applications and classifiers for sentiment analysis-SciEngine .
2. Basani . Application of Sentiment Analysis on Product Review (E-Commerce). Y. Basani (Yuniarta Basani), “Application of Sentiment
Analysis on Product Review E-Commerce,” (conference/technical report), 2019. Available on (PDF) Application of Sentiment
Analysis on Product Review E-Commerce .
3. He & al. Exploring E-Commerce Product Experience Based on Fusion Sentiment Analysis Method. He, Zhou & Zhao (authors listed
in several copies), “Exploring E-Commerce Product Experience Based on Fusion Sentiment Analysis Method,” Res Militaris /
conference article (online), 2022–2024 (published copies vary by repository). Available on RES MILITARIS .
4. Demircan & al. Developing Turkish sentiment analysis models using machine learning and e-commerce data . M. Demircan, A. Seller,
F. Abut, M. F. Akay, International Journal of Cognitive Computing in Engineering, Vol. 2, pp. 202–207, 2021. Available on
Developing Turkish sentiment analysis models using machine learning and e-commerce data - ScienceDirect .
5. Pang & Lee .Opinion Mining and Sentiment Analysis (survey / foundational methods). Bo Pang & Lillian Lee, “Opinion Mining and
Sentiment Analysis,” Foundations and Trends in Information Retrieval (survey), 2008. Available on omsa.pdf . [6] M. Exwell,
“Women’s E-Commerce Clothing Reviews Dataset,” Kaggle, 2018. [Online]. Available at:
https://www.kaggle.com/datasets/mexwell/womens-e-commerce clothing-reviews
Deshakulkarni Suresh, et al., Global Transitions Proceedings, Vol. 2, Issue 2, pp. 205–211, 2021. Available on Comparative study of
various approaches, applications and classifiers for sentiment analysis-SciEngine .
2. Basani . Application of Sentiment Analysis on Product Review (E-Commerce). Y. Basani (Yuniarta Basani), “Application of Sentiment
Analysis on Product Review E-Commerce,” (conference/technical report), 2019. Available on (PDF) Application of Sentiment
Analysis on Product Review E-Commerce .
3. He & al. Exploring E-Commerce Product Experience Based on Fusion Sentiment Analysis Method. He, Zhou & Zhao (authors listed
in several copies), “Exploring E-Commerce Product Experience Based on Fusion Sentiment Analysis Method,” Res Militaris /
conference article (online), 2022–2024 (published copies vary by repository). Available on RES MILITARIS .
4. Demircan & al. Developing Turkish sentiment analysis models using machine learning and e-commerce data . M. Demircan, A. Seller,
F. Abut, M. F. Akay, International Journal of Cognitive Computing in Engineering, Vol. 2, pp. 202–207, 2021. Available on
Developing Turkish sentiment analysis models using machine learning and e-commerce data - ScienceDirect .
5. Pang & Lee .Opinion Mining and Sentiment Analysis (survey / foundational methods). Bo Pang & Lillian Lee, “Opinion Mining and
Sentiment Analysis,” Foundations and Trends in Information Retrieval (survey), 2008. Available on omsa.pdf . [6] M. Exwell,
“Women’s E-Commerce Clothing Reviews Dataset,” Kaggle, 2018. [Online]. Available at:
https://www.kaggle.com/datasets/mexwell/womens-e-commerce clothing-reviews
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