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http://dx.doi.org/10.9708/jksci.2020.25.03.207

Methodology for Identifying Key Factors in Sentiment Analysis by Customer Characteristics Using Attention Mechanism  

Lee, Kwangho (Graduate School of Business IT, Kookmin University)
Kim, Namgyu (School of Management Information Systems, Kookmin University)
Publication Information
Journal of the Korea Society of Computer and Information / v.25, no.3, 2020 , pp. 207-218 More about this Journal
Abstract
Recently, due to the increase of online reviews and the development of analysis technology, the interest and demand for online review analysis continues to increase. However, previous studies have not considered the emotions contained in each vocabulary may differ from one reviewer to another. Therefore, this study first classifies the customer group according to the customer's grade, and presents the result of analyzing the difference by performing review analysis for each customer group. We found that the price factor had a significant influence on the evaluation of products for customers with high ratings. On the contrary, in the case of low-grade customers, the degree of correspondence between the contents introduced in the mall and the actual product significantly influenced the evaluation of the product. We expect that the proposed methodology can be effectively used to establish differentiated marketing strategies by identifying factors that affect product evaluation by customer group.
Keywords
Attention Mechanism; Big Data; Deep Learning; Review Analysis; Text Analytics;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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