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Sentimental Analysis of Online Reviews Using Fuzzy Sets and Rough Sets

Sentimental Analysis of Online Reviews Using Fuzzy Sets and Rough Sets
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Author(s): Anuradha Jagadeesan (VIT University, India)and Amit Patil (VIT University, India)
Copyright: 2017
Pages: 19
Source title: Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making
Source Author(s)/Editor(s): Arun Kumar Sangaiah (VIT University, India), Xiao-Zhi Gao (University of Eastern Finland, Finland)and Ajith Abraham (Machine Intelligence Research Labs, USA)
DOI: 10.4018/978-1-5225-1008-6.ch017

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Abstract

With the increased interest of online users in E-commerce, the web has become an excellent source for buying and selling of products online. Customer reviews on the web help potential customers to make purchase decisions, and for manufacturers to incorporate improvements in their product or develop new marketing strategies. The increase in customer reviews of a product influence the popularity and the sale rate of the product. This lead to a very important question about the analysis of the sentiments (opinions) expressed in the reviews. As such internet does not have any quality control over customer reviews and it could vary in terms of its quality. Also the trustworthiness of the online reviews is debatable. Sentiment Analysis (SA) or Opinion Mining is the computational analysis of opinions, sentiments, emotions and subjectivity of text. In this chapter, we take a look at the various research challenges and a new dimension involved in sentiment analysis using fuzzy sets and rough sets.

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