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The Scientific World Journal
Volume 2014, Article ID 340583, 9 pages
Research Article

Critical Product Features’ Identification Using an Opinion Analyzer

1Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia
2COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
3Federal Urdu University of Arts, Science and Technology, Islamabad 44000, Pakistan

Received 21 May 2014; Revised 4 September 2014; Accepted 15 September 2014; Published 24 November 2014

Academic Editor: Christian Baumgartner

Copyright © 2014 Azra Shamim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer’s reviews. Online consumer’s reviews present tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers’ reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers’ reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers’ feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly.