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A Sentiment Classification Method Using Context Information in Product Review Summarization  

Yang, Jung-Yeon (서울대학교 컴퓨터공학부)
Myung, Jae-Seok (서울대학교 컴퓨터공학부)
Lee, Sang-Goo (서울대학교 컴퓨터공학부)
Publication Information
Journal of KIISE:Databases / v.36, no.4, 2009 , pp. 254-262 More about this Journal
Abstract
As the trend of e-business activities develop, customers come into contact with products through on-line shopping sites and lots of customers refer product reviews before the purchasing on-line. However, as the volume of product reviews grow, it takes a great deal of time and effort for customers to read and evaluate voluminous product reviews. Lately, attention is being paid to Opinion Mining(OM) as one of the effective solutions to this problem. In this paper, we propose an efficient method for opinion sentiment classification of product reviews using product specific context information of words occurred in the reviews. We define the context information of words and propose the application of context for sentiment classification and we show the performance of our method through the experiments. Additionally, in case of word corpus construction, we propose the method to construct word corpus automatically using the review texts and review scores in order to prevent traditional manual process. In consequence, we can easily get exact sentiment polarities of opinion words in product reviews.
Keywords
Opinion Mining; Sentiment Classification; Product review summarization; Context information; e-business; Product Information;
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