Product opinion analysis using text mining and analysis. (2018)

• Record Type: Journal Article
• Authors: Marimuthu, K.; Shankar, Anuj; Ranganathan, Rashmi; Niranchana, R.
• Is Part Of: International journal of smart grid and green communications. Volume 1:Number 3(2018)
• Page Start: 227
• Page End: 234
• Publication Date: 2018
• Subjects: review analysis -- user registration -- dashboard -- NLP -- overview of product -- text mining; Smart power grids -- Computer networks -- Periodicals; Smart power grids -- Periodicals; Wireless communication systems -- Security measures -- Periodicals; Wireless communication systems -- Energy consumption -- Periodicals; 333.7911028546
• Languages: English
• ISSNs: 2052-2002

Abstract

The enormous growth and usage of e-commerce offer positive ways to any business by sharing the emotions, feelings and experiences. Web users are benefited with valuable online reviews. There are many instances, where these reviews are not considered for evaluation of a product in the market, thus affecting the sales of the products. We intend to solve the problem of sentiment polarity computation, which is one of the most basic problems of sentiment analysis. A general process for sentiment polarity computation, department wise classification and feature extraction is proposed with detailed procedure. Data on online product reviews from Amazon.com was used in this study. ProSent is a real-time web service, which provides insights of the product by applying sentiment analysis on the reviews. It eases the way to manage bulk customer reviews and also simplifies handling of customer reviews with customisable workflow processes and meaningful graphs and charts.