摘要
【目的】解决单纯使用评论长度衡量在线商品评论深刻性的问题。【方法】提出一种在线商品评论深刻性度量模型。在分析消费者制定购买决策所需信息本质的基础上,定义评论深刻性概念,并引入商品特征概念树。依据领域专家发表商品评论的特点以及评论中商品特征在商品特征概念树中的分布性,建立商品评论深刻性度量评价模型。【结果】通过实证研究证实深刻性度量模型与现有的评论有效性模型相一致,表明该模型的可行性。【局限】未涉及消费者对商品使用场景的描述,缺少对体验型商品的评论深刻性度量研究。【结论】在线商品评论的深刻性模型能够比较准确地评价商品评论的深度。
[Objective] Solve the problem which only use the length of online product review to measure the review depth. [Methods] In this paper, a metrics-model for online product review depth is proposed. Firstly, on the basis of analyzing the demand information of customers for making decision, the concept of review depth is defined and feature concept tree of product is introduced. Secondly, the metrics-model for measuring product review depth is presented according to the features of the product review from domain experts and the distribution of product features over feature concept tree of product. [Results] Empirical study demonstrates that the metrics-model is identical to the model for review helpfulness, and the result shows that the model is feasible. [Limitations] This paper does not involve the product usage scenario of consumers and the review depth measurement for experience products. [Conclusions] The metrics-model can measure product review depth more accuratelv.
出处
《现代图书情报技术》
CSSCI
2015年第9期17-25,共9页
New Technology of Library and Information Service
基金
国家自然科学基金项目"C2C市场中基于行为树的销量识别与发布研究"(项目编号:71371012)
教育部人文社会科学规划项目"C2C市场中基于参与者行为的‘打榜’识别模型与应用研究"(项目编号:13YJA630098)的研究成果之一
关键词
商品评论
评论深刻性
商品特征概念树
特征概念分布
度量模型
Product review Review depth Feature concept tree of product Distribution of feature concept Metrics-Model
