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ÇѱÛÁ¦¸ñ(Korean Title) |
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¿µ¹®Á¦¸ñ(English Title) |
A Technique for Product Effect Analysis Using Online Customer Reviews |
ÀúÀÚ(Author) |
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So Yeong Lee
Ji Na Lee
Bo Kyung Ryu
Hyon Hee Kim
±èÇöÈñ
Young Seo Lim
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¿ø¹®¼ö·Ïó(Citation) |
VOL 09 NO. 09 PP. 0259 ~ 0266 (2020. 09) |
Çѱ۳»¿ë (Korean Abstract) |
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¿µ¹®³»¿ë (English 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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Å°¿öµå(Keyword) |
Á¦Ç° È¿°ú ºÐ¼®
È¿°ú ÃøÁ¤ ¾Ë°í¸®Áò
Product Effectiveness Analysis
Effectiveness Measurement Algorithm
Online Customer Review
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