Abstract—Social commerce market, which is promoted using a social network service, is getting bigger with the activation of a social network service. If a number of consumers are more than a number which the sellers decide before selling, the deal in social commerce market is completed. It’s actually hard to guarantee money back regarding the reason, so reviews are very important to effect for purchasing the products in social commerce market. It may have different direction of information through background, taste, emotion of the reviewers. At the same time, if the meaning of text information can be extracted, we can have the correct information that we need. This paper shows that we extract the meaning by opinion mining and identifying the user’s basic information and psychological state by LIWC. It gives the correct ratings to consumers who want to purchase products through social commerce market. Also it can be helpful to increase reliability of opinion mining on the other fields.
Index Terms—Social commerce, opinion mining, LIWC, ratings
The authors are with the Information and Communication Engineering Sung Kyun Kwan University 440-746 Suwon, Korea (Tel.: + 82312907218; fax: +82312907219; e-mail: {01039374479,vntlffl, uk3080789}@naver.com, umkim@ece.skku.ac.kr).
Cite: Ji Yeon Lim, Jae Yoel Yoon, Lee Joon Kim, and Ung Mo Kim, "Information Extraction of Review Using LIWC," International Journal of Future Computer and Communication vol. 1, no. 2, pp. 91-93, 2012.
Copyright © 2008-2024. International Journal of Future Computer and Communication. All rights reserved.
E-mail: ijfcc@ejournal.net