什么样的评论更容易获得有用性投票——以亚马逊网站研究为例

Identifying Reviews with More Positive Votes——Case Study of Amazon.cn

【目的】购物网站评论系统中的投票机制有利于帮助消费者筛选出高质量评论。本文以评论有用性投票数为研究对象,探讨什么样的评论更容易获得有用性投票。【方法】以信息采纳理论和负面偏差理论为基础,基于亚马逊购物网站中的12 393条手机评论数据,结合文本分析与零膨胀负二项回归分析方法,从评论者信度、评论信息质量、评论极性三个方面探究评论有用性投票影响因素。【结果】研究结果表明,评论者有用性、评论信息量、评论回复数、极端评分、评论文本消极倾向对评论有用性投票数具有积极正向影响。评论者发表评论数、评论者是否确认购买对评论有用性投票数有负向影响。【局限】仅以手机这一搜索型产品为研究对象,研究结果欠缺普适性。【结论】本文研究成果对于改善电子商务评论排序系统具有借鉴意义。

[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.