Title :
An Ontology-Based Sentiment Classification Methodology for Online Consumer Reviews
Author :
Polpinij, Jantima ; Ghose, Aditya K.
Author_Institution :
Decision Syst. Lab., Univ. of Wollongong, Wollongong, NSW
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.
Keywords :
ontologies (artificial intelligence); support vector machines; text analysis; lexical variable ontology; online consumer reviews; ontology-based sentiment classification methodology; support vector machines; text classification approach; Automotive engineering; Electronic commerce; Intelligent agent; Internet; Motion pictures; Ontologies; Support vector machine classification; Support vector machines; Text categorization; Web search; lexical variable ontology; online product reviews; sentiment classification; support vector machines;
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
DOI :
10.1109/WIIAT.2008.68
