在线商品评论有用性影响因素研究:基于文本语义视角被引量：17

Impact Factors of Online Customer Reviews Usefulness: A Text Semantics Approach

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摘要针对在线商品评论总体质量不高、缺乏有效评论引导机制的问题,以亚马逊商品在线评论为研究对象,结合文本挖掘技术和实证研究,探究基于文本内容评论有用性的影响因素。通过以手机这一典型商品为例,发现消费者关注手机系统反应、音质、导航、打字体验,希望了解电池、充电器等配件细节,重视商家的配送、退换货、保修、发票等服务,评论文本包含这些信息会提高其有用性。 In view of the problem of low quality and lacking effective guidance mechanism in online review systems, this paper takes product reviews from www. Amazon. cn as the subject and explores the factors influencing review usefulness based on the text content, using text mining and empirical research methods. Taking the mobile phone as an example, the authors find that consumers pay atten- tion to the handset system reaction, acoustic fidelity, GPS, typing experience, and hope knowing accessories such as battery, battery charger, business＇ s allocation, exchanging products services, maintenance, and receipts. If some of these factors are mentioned, the reviews will be more useful for later customers.

作者陈江涛张金隆张亚军

机构地区华中科技大学管理学院长江大学管理学院

出处《图书情报工作》 CSSCI 北大核心 2012年第10期119-123,共5页 Library and Information Service

基金国家自然科学基金重点项目"移动商务的基础理论与技术方法研究"(项目编号:70731001)研究成果之一

关键词在线商品评论文本挖掘潜在语义分析 online product reviews text mining latent semantic analysis

分类号 G203 [文化科学—传播学]

作者简介陈江涛，男，1980年生，讲师．博士研究生。发表论文4篇。张金隆，男，1952年生，教授，博士生导师，发表论文120余篇。张亚军，男，1984年生，博士研究生。

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