A Technique for Product Effect Analysis Using Online Customer Reviews


KIPS Transactions on Software and Data Engineering, Vol. 9, No. 9, pp. 259-266, Sep. 2020
https://doi.org/10.3745/KTSDE.2020.9.9.259, Full Text:
Keywords: Product Effectiveness Analysis, Effectiveness Measurement Algorithm, Online Customer Review
Abstract

In this paper, we propose a novel scheme for product effect analysis, termed PEM, to find out the effectiveness of products used for improving the current condition, such as health supplements and cosmetics, by utilizing online customer reviews. The proposed technique preprocesses online customer reviews to remove advertisements automatically, constructs the word dictionary composed of symptoms, effects, increases, and decreases, and measures products’ effects from online customer reviews. Using Naver Shopping Review datasets collected through crawling, we evaluated the performance of PEM compared to those of two methods using traditional sentiment dictionary and an RNN model, respectively. Our experimental results shows that the proposed technique outperforms the other two methods. In addition, by applying the proposed technique to the online customer reviews of atopic dermatitis and acne, effective treatments for them were found appeared on online social media. The proposed product effect analysis technique presented in this paper can be applied to various products and social media because it can score the effect of products from reviews of various media including blogs.


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Cite this article
[IEEE Style]
Y. S. Lim, S. Y. Lee, J. N. Lee, B. K. Ryu and H. H. Kim, "A Technique for Product Effect Analysis Using Online Customer Reviews," KIPS Transactions on Software and Data Engineering, vol. 9, no. 9, pp. 259-266, 2020. DOI: https://doi.org/10.3745/KTSDE.2020.9.9.259.

[ACM Style]
Young Seo Lim, So Yeong Lee, Ji Na Lee, Bo Kyung Ryu, and Hyon Hee Kim. 2020. A Technique for Product Effect Analysis Using Online Customer Reviews. KIPS Transactions on Software and Data Engineering, 9, 9, (2020), 259-266. DOI: https://doi.org/10.3745/KTSDE.2020.9.9.259.