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http://dx.doi.org/10.7838/jsebs.2011.16.4.125

Product Review Data and Sentiment Analytical Processing Modeling  

Yeon, Jong-Heum (서울대학교 컴퓨터공학부)
Lee, Dong-Joo (삼성전자 DMC연구소)
Shim, Jun-Ho (숙명여자대학교 컴퓨터과학부)
Lee, Sang-Goo (서울대학교 컴퓨터공학부)
Publication Information
The Journal of Society for e-Business Studies / v.16, no.4, 2011 , pp. 125-137 More about this Journal
Abstract
Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.
Keywords
Sentiment Analysis; Opinion Mining; OLAP; Data Warehouse;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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