商家的操纵评论行为对在线评论真实性影响研究被引量：9

The Influence of Seller's Manipulation of Online Reviews

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摘要从商家操纵商品评论的视角出发,证明了该行为的存在性并建立模型反映该行为的影响。提出了纠正偏差的方法并给出算例。研究发现,以淘宝网为代表的C2C电子商务存在商家操纵好评的行为,在这种行为的作用下,在线评论得分及好评率随时间呈下降趋势。通过模型计算得出反映商品真实质量的得分并经数据拟合获得了反映买家操纵评论行为概率的曲线方程。 This paper firstly documents the existence of online review manipulation and its features plus the influence mecha- nism on online reviews bias. The research finds that C2C e-business do exist the seller＇s manipulation. Besides, the manip- ulation may decrease over time so as to make the online review＇s rating and the positive feedback rate follow the same decrea- sing trend. In order to correct the bias, the paper constructs and solves the online review model using the Taobao＇s empirical data, derives the true rating and the curvilinear equation of the seller＇s manipulation probability.

作者李雨洁李苑凌

机构地区西南政法大学管理学院

出处《软科学》 CSSCI 北大核心 2015年第12期135-139,共5页 Soft Science

基金国家社会科学基金项目(12CGL049) 教育部人文社会科学青年基金项目(15YJC630068) 重庆市社会科学规划博士资助项目(2014BS106)

关键词在线评论偏差商家操纵行为 online review bias seller＇s manipulation

分类号 F713.36 [经济管理—产业经济]

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参考文献10

1Cheung M Y,Luo C,Sia C L,et al.Credibility of Electronic Word of Mouth:Informational and Normative Determinants of On-Line Consumer Recommendations[J].International Journal of Electronic Commerce,2009,13(4):9-38.
2Ong T,Mannino M,Gregg D.Product Reputation Manipulation:The Impact of Shill Reviews on Perceived Quality[C].Proceedings of Nineteenth Americas Conference on Information Systems,Chicago,Illinois,2013.15-17.
3Lam S K,Riedl J.Shilling Recommender Systems for Fun and Profit[C].Proceedings of the 13th International Conference on World Wide Web,2004.393-402.
4Hu N,Bose I,Gao Y J,et al.Manipulation in Digital Word of Mouth:A Reality Check for Book Reviews[J].Decision Support Systems,2011,50(3):627-635.
5Mayzlin D.Promotional Chat on the Internet[J].Marketing Science,2006,25(2):155-163.
6Duan H,Zirn C.Can We Identify Manipulative Behavior and the Corresponding Suspects on Review Websites Using Supervised Learning?[J].Secure IT Systems,2012:215-230.
7Mayzlin D,Dover Y,Chevalier J A.Promotional Reviews:An Empirical Investigation of Online Review Manipulation[C].National Bureau of Economic Research Working Paper,2013.18340.
8Hu N,Liu L,Sambamurthy V.Fraud Detection in Online Consumer Reviews[J].Decision Support Systems,2011,50(3):614-626.
9李雨洁,廖成林,于辉.线上商品评论反“L”型分布的偏差与纠正[J].统计研究,2013,30(4):46-51. 被引量：7
10李雨洁,廖成林,李忆.消费者个体行为偏好对在线评论真实性的影响机理研究[J].软科学,2015,29(1):105-109. 被引量：3

二级参考文献33

1彭惠,王永瑞.C2C电子商务市场整体卖家信用分布研究[J].情报杂志,2012,31(5):122-127. 被引量：21
2P Y Chen, S Y Wu, J Yoon. The impact of online recommendations and consumer feedback on sales [ C ]. Proceedings of the International Conference on Information Systems Washington,2004 : 711-724.
3Liu, Yong. Word-of-Mouth for movies: Its dynamics and impact on box office revenue[ J ]. Journal of Marketing, 2006 (3) : 74-89.
4J A Chevalier, D Mayzlin. The effect of word of mouth on sales: Online book reviews [ J ]. Marketing Research,2006 (3) : 345-354.
5X Li, L M Hitt. Self selection and information role of online product reviews[ J]. Information Systems Research, 2008 (4) : 456-474.
6N Hu, P Pavlou, J Zhang. Overcoming the J-shaped distribution of product reviews [ J ]. Communications of the ACM, 2009 ( 10 ) : 144-147.
7N Archak, A Ghose, P G lpeirotis. Deriving the pricing power of product features by mining consumer reviews [ J ]. Management Science, 2011 ( 8 ) : 1485-1509.
8!N Awad, F R Arik. Establishing trust in electronic commerce through online word of mouth: An examination across genders [ J ]. Journal of Management Information System, 2008 (4) : 101-121.
9L Stelio, H Andrew. A Bayesian model of how people search online consumer reviews[ J]. Cognitive Science Society, 2008 : 553-558.
10A Jensen. How much can we boost IQ and scholastic achievement?[J]. Harvard Educational Review, 1969( 1 ) : 1-123.