Main Article Content

Abstract

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.

Keywords

Sentiment analysis, product reviews, naive bayes

Article Details

How to Cite
[1]
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.

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