BibTeX:

@article{IJIRSTV3I12064,
     title={A Study and Comparison on Sentiment Analysis for the Products Available in E- Commerce},
     author={S.Muthukumaran},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={12},
     pages={191--195},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I12064.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

This paper explains different methods for sentiment analysis and showcases an efficient methodology. It also highlights the importance the product reviews are of utmost importance for the buyers to decide based on their concerns regarding product's various aspects for example a monitor, processor speed, memory etc. Hence this sentiment analysis of product review provides nearly accurate statistics regarding a product, providing an ease to the customers for analyzing the product and zero down his/her search for an online product. The key focus here is efficient feature extraction, polarity classification thereby summarizing positive and negative or neutral polarity. The proposed work is able to collect information from various sites and perform a sentiment analysis of a user reviews based on that information to rank a product. Also these reviews suffer from spammed reviews from unauthenticated users. So to avoid this confusion and make this review system more transparent and user friendly we propose a technique to extract feature based opinion from a diverse pool of reviews and processing it further to segregate it with respect to the aspects.

Sentiment Analysis, Python Language, Products, Opinion Mining, Natural language processing