Analyzing and AssessingReviews on Jd.com
Analyzing and AssessingReviews on Jd.com
复制标题
分析和评估京东的评论
DOI：
10.1080/10798587.2016.1267244
复制
发表时间：
--
影响因子：
2
通讯作者：
Yunchuan Sun
中科院分区：
文献类型：
--
作者：
Jie Liu;Xiaodong Fu;Jin Liu;Yunchuan Sun
评论是用户对产品或服务表达意见的内容。评论中包含的信息对于将要对产品或服务做出决定的用户是有价值的。然而，流行产品有很多评论，而且评论的质量并不总是好的。有必要从众多评论中挑选出高质量的评论，以帮助用户做出决策。在本文中，我们从京东的499253个产品中收集了21,501条被标记为好的评论。我们观察到用户的水平是影响评论质量的重要因素，用户更喜欢发布包含产品质量和价格描述的简短评论。在本文中，我们提出了一个自动评估评审质量的系统。我们通过应用基于两类特征的SVM分类实现了这一目标；能够帮助用户从大量评论中找到高质量评论和有用信息的评论和评论者。我们在京东上评估了我们的系统。我们的实验对评审质量评估的准确率达到87.5%。
Reviews are contents written by users to express opinions on products or services. The information contained in reviews is valuable to users who are going to make decisions on products or services. However, there are numbers of reviews for popular products, and the quality of reviews is not always good. It’s necessary to pick out reviews, which are in high quality from numbers of reviews to assist user in making decision. In this paper, we collected 21,501 reviews flagged as good from 499,253 products on JD.com. We observed the level of users is an important factor affects the quality of reviews, and users prefer to post short reviews containing the description of the quality and price of the product. We proposed a system to assess the quality of reviews automatically in this paper. We achieved that by applying SVM classification based on two kinds of features; reviews and reviewers that would help users find out high quality reviews and useful information from massive reviews. We evaluated our system on JD.com. The accuracy of our experiments for reviews quality assessing reached to 87.5 percent.