Performance Evaluation of Review Spam Detection for a Domestic Shopping Site Application 


Vol. 44,  No. 4, pp. 339-343, Apr.  2017


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  Abstract

As the number of customers who write fake reviews is increasing, online shopping sites have difficulty in providing reliable reviews. Fake reviews are called review spam, and they are written to promote or defame the product. They directly affect sales volume of the product; therefore, it is important to detect review spam. Review spam detection methods suggested in prior researches were only based on an international site even though review spam is a widespread problem in domestic shopping sites. In this paper, we have presented new review features of the domestic shopping site NAVER, and we have applied the formerly introduced method to this site for performing an evaluation.


  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

J. Park and C. Kim, "Performance Evaluation of Review Spam Detection for a Domestic Shopping Site Application," Journal of KIISE, JOK, vol. 44, no. 4, pp. 339-343, 2017. DOI: .


[ACM Style]

Jihyun Park and Chong-kwon Kim. 2017. Performance Evaluation of Review Spam Detection for a Domestic Shopping Site Application. Journal of KIISE, JOK, 44, 4, (2017), 339-343. DOI: .


[KCI Style]

박지현, 김종권, "국내 쇼핑 사이트 적용을 위한 리뷰 스팸 탐지 방법의 성능 평가," 한국정보과학회 논문지, 제44권, 제4호, 339~343쪽, 2017. DOI: .


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