Title: Fine-grained opinion mining of product review using sentiment and semantic orientation

Authors: Gaurav Dubey; Ajay Rana; Jayanthi Ranjan

Addresses: Amity University, Sec 125, Noida UP, India ' Amity University, Sec 125, Noida UP, India ' IMT, Ghaziabad, India

Abstract: The reviews or feedback about a product or service has become quite significant in marketing, promoting, or improvising the product or service, since e-commerce, or purchasing of online products, has recently become a trend. The availability of product reviews is online and in the form of text but these reviews are very much in an unstructured form, which does not help either the new consumer, or the organisation, to take any decision further. In this paper, we have proposed an approach based on opinion mining and sentiment analysis. We have explored the sentiment orientation and sentiment classification to evaluate the customers' review. The reviews of various mobiles were converted from unstructured to structure to extract the summarised knowledge from online reviews. The number of user reviews was explored and the empirical results found that the sentiment orientation and classification provides the effective methods for better decision-making and benchmarking.

Keywords: online reviews; iphones; semantic orientation; opinion mining; sentiment analysis; online feedback; product reviews; sentiment classification; customers reviews; mobile phones; cell phones.

DOI: 10.1504/IJBIS.2017.083274

International Journal of Business Information Systems, 2017 Vol.25 No.1, pp.1 - 17

Received: 01 Jun 2015
Accepted: 28 Aug 2015

Published online: 16 Mar 2017 *

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