基于在线评级和评论的评价者效用机制研究

发布时间：2018-11-05 21:11

【摘要】：互联网中对产品和服务的评价越来越受到重视,因为评价能够消除消费者的不确定性,辅助其做出购买决策。大多数在线购物网站中用户的评价包括评级和评论。现有的评价反馈系统和评价研究往往只单独关注评价者之间的评级或评论,而忽略了两者之间的有机统一。评价者的评级并不一定反映评价者的真实评价,很多评价者更倾向于选择评论文本来表达自己的真实情感。本文以从淘宝网抓取的852071条评价数据为基础,通过分析评价者评级和评论之间的不一致性,结合RFM模型,考虑评级和评论两种信息形成的评价效用,提出了RFMA模型来计算评价者的总体评价效用。并据此对好的与不好的评价者进行区分,进一步为消费者的购买决策提供支持。通过对评价者的总体分析可以得出,本文提出的机制更加具有可用性和有效性。
[Abstract]:More and more attention has been paid to the evaluation of products and services on the Internet because it can eliminate the uncertainty of consumers and help them to make purchase decisions. Most online shopping sites include ratings and reviews. The existing evaluation feedback system and evaluation research usually only pay attention to the rating or comment between the evaluators, but ignore the organic unity between the two. The rating of the evaluator does not necessarily reflect the true evaluation of the evaluator. Many reviewers prefer to choose the comment text to express their true feelings. Based on the 852071 evaluation data collected from Taobao, this paper analyzes the inconsistency between the rating of the evaluator and the comment, combined with the RFM model, and considers the evaluation utility formed by the two kinds of information: rating and comment. A RFMA model is proposed to calculate the overall evaluation utility of the evaluators. According to the distinction between good and bad evaluators, it provides further support for consumers' purchase decisions. Through the overall analysis of the evaluators, it can be concluded that the mechanism proposed in this paper is more available and effective.
【作者单位】：中国人民大学信息学院;中科院科技政策与管理科学研究所;
【基金】：国家自然科学基金资助项目(71531012,71271211) 京东商城电子商务研究项目(413313012) 北京市自然科学基金资助项目(4132067) 中国人民大学品牌计划项目(10XNI029)
【分类号】：F724.6

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