Main Article Content


In the digitalized world recommendation of any products to attract customers that meet their requirements is very crucial for the vendors to survive in the global market. Sentiment analysis is an intellectual way of identifying user’s sentiments towards certain entities. Natural Language Processing (NLP) has the process of analyzing sentiments as one of its prominent fields. In today’s e-commerce world sentiment analysis is crucial part because it capture the opinion of any product. The growth in e-commerce has led to increasing customer reviews about various products which are available on the internet. Reviews are not only for product but also the service given to the customer. The objective is that identifying set potential feature in the review and extracting review. The approach proposed in this paper is novel and serves as a better alternative to rate a product based on its technical specification by analyzing large number of user reviews which are the subjective information in source materials i.e. e-commerce website by applying Natural Language processing, . Several methods have been developed in recent years in order to accomplish this task. In this paper, we discuss various levels of sentiment analysis followed by comparison among different approaches to sentiment analysis.


Sentiment analysis, product reviews, naive bayes

Article Details

How to Cite
Prof. Swati Powar, Mr. Sonu Parab, Mr. Sahil Panchal, and Mr. Siddesh Parkar, “SENTIMENT ANALYSIS ON PRODUCT REVIEWS”, IEJRD - International Multidisciplinary Journal, vol. 5, no. 5, p. 6, Jun. 2020.


  1. Ms. Swati Powar, Dr. Subhash Shinde “Named Entity Recognition and Tweet Sentiment Derived From Tweet Segmentation using Hadoop”, IEEE & CSI sponsored 1st International Conference on Intelligent Systems & Information Management Oct.2017.
  2. Sayali Pednekar, Komal Patil, Rutweek Sawant “SENTIMENT ANALYSIS ON ONLINE PRODUCT REVIEWS” International Journal of Research Education.
  3. Prashant Kumar Singh, Arjit Sachdeva, Dhruv Mahajan, Nishtha Pande, Amit Sharma “An approach towards feature specific opinion mining and sentimental analysis across ecommerce websites”, 5th International Conference- Confluence the Next Generation Information Technology Summit, (Confluence) 2014.
  4. Anil Singh Parihar, Bhagyanidhi. “A Study on Sentiment Analysis of Product Reviews” 2018 International Conference on Soft-computing and Network Security (ICSNS).
  5. A.Nisha Jebaseeli,, E.Kirubakarm.” A Survey on Sentiment Analysis of (Product) Reviews”International Journal of computer
  6. Applications (0975 – 888) Volume 47– No.11, June 2012.
  7. Raheesa Safrin, K.R.Sharmila, T.S.Shri Subangi, E.A.Vimal “SENTIMENT ANALYSIS ON ONLINE PRODUCT REVIEW” in International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 04 | Apr -2017
  8. Periakaruppan Sudhakaran, S hanmugasundaram Hariharan “Classifying product reviews from balanced datasets for Sentiment Analysis and Opinion Mining”, Joan Lu3 in 2014 6th International Conference on Multimedia, Computer Graphics and Broadcasting
  9. Santhosh Kumar K L, Jayanti Desai, Jharna Majumdar, “Opinion Mining and Sentiment Analysis on Online Customer Review” 2016 IEEE International Conference on Computational Intelligence and Computing Research