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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (9): 16-27    DOI: 10.11925/infotech.2096-3467.2017.09.02
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Identifying Reviews with More Positive Votes——Case Study of Amazon.cn
Jiang Wu,Wanwan Liu
School of Information Management, Wuhan University, Wuhan 430072, China
The Center of E-commerce Research and Development of Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] This article examines online reviews attracting more positive votes from consumers, aiming to identify those high quality reviews based on the information adoption and negative bias theories. [Methods] First, we retrieved 12 393 reviews on cellphones from Amazon.cn. Then, we investigated the impacts of the review’s characteristics on the numbers of positive votes with the help of zero inflated negative binomial regression and text analysis methods. The characteristics we studied include reviewer’s credibility, review’s quality and extremity. [Results] The usefulness of the reviewer’s previous posting, the information quality of the reviews, the number of comments, the extreme ratings, and the negative level of the reviews helped them receive more positive votes. However, the reviewers bought the products or not, and the number of the previously posted reviews had negative influence on the number of votes. [Limitations] Only investigated cellphones in this study. [Conclusions] This paper helps E-commerce websites improve their review ranking algorithms.

Key wordsOnline Review      Online Review Helpfulness      Review Vote     
Received: 23 May 2017      Published: 18 October 2017

Cite this article:

Jiang Wu,Wanwan Liu. Identifying Reviews with More Positive Votes——Case Study of Amazon.cn. Data Analysis and Knowledge Discovery, 2017, 1(9): 16-27.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.09.02     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I9/16

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