An ontology-based sentiment classification methodology for online consumer reviews

Authors

Jantima Polpinij, University of WollongongFollow
Aditya K. Ghose, University of WollongongFollow

RIS ID

27539

Publication Details

Polpinij, J. & Ghose, A. K. (2008). An ontology-based sentiment classification methodology for online consumer reviews. IEEE/WIC/ACM International Conference on Intelligent Agent Technology (pp. 518-524). IEEE Explore Online: ieeexplore.ieee.org: Institute of Electrical and Electronics Engineers ( IEEE ).

Abstract

This paper presents a method of ontology-based sentiment classification to classify and analyse online product reviews of consumers. We implement and experiment with a support vector machines text classification approach based on a lexical variable ontology. After testing, it could be demonstrated that the proposed method can provide more effectiveness for sentiment classification based on text content.