A feature-opinion extraction approach to opinion mining

Authors:
Bolanle A. Ojokoh;Olumide Kayode
Affiliations:
Department of Computer Science, Federal University of Technology, Akure, Nigeria;Department of Computer Science, Federal University of Technology, Akure, Nigeria
Venue:
Journal of Web Engineering
Year:
2012

Citing 10
Cited 0

Mining the peanut gallery: opinion extraction and semantic classification of product reviews

WWW '03 Proceedings of the 12th international conference on World Wide Web
Measuring praise and criticism: Inference of semantic orientation from association

ACM Transactions on Information Systems (TOIS)
Mining and summarizing customer reviews

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion observer: analyzing and comparing opinions on the Web

WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Extracting product features and opinions from reviews

HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Recognizing contextual polarity in phrase-level sentiment analysis

HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A holistic lexicon-based approach to opinion mining

WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
A novel lexicalized HMM-based learning framework for web opinion miningNOTE FROM ACM: A Joint ACM Conference Committee has been determined that the authors of this article violated ACM's publication policy on simultaneous submissions. Therefore ACM has shut off access to this paper.

ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Recommended or Not Recommended? Review Classification through Opinion Extraction

APWEB '10 Proceedings of the 2010 12th International Asia-Pacific Web Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the rapid expansion of the web and e-commerce in recent times, increasingly numerous products are bought and sold on the Web. A lot of product reviews which would be very useful for potential customers to make better decisions are generated by web users. It is highly essential to produce a correct and quick summary of these reviews. In this paper, we propose a method that extracts feature and opinion pairs from online reviews, determines the polarity and strength of these opinions with the aim of summarizing and determining the recommendation status of the customers' reviews. The evaluation results on opinion extraction from the reviews of digital camera demonstrate the effectiveness of the proposed technique.