摘要
买家在线评论是顾客考核商家信任度的重要依据,对买家评论文本进行分析具有重要意义。为更加准确地分析评论信息内容,挖掘其真实推荐价值,可从评论文本分析着手构建新的信任推荐模型。一方面,针对好、中、差三类评论与所对应评论内容不匹配的现象,构建评论文本中心度因子和评论情感因子,同时综合考虑交易时间、金额等因素,引入反馈机制,建立一种全面客观的推荐模型;另一方面,结合算法编程对模型进行模拟仿真实现,有效挖掘评论的真实推荐价值,提高计算所得信任值对买家决策的参考价值和推荐的可靠性。根据该模型研究结果,为更好地帮助电商提高推荐信任度,帮助买家进行购买决策,对电商和在线平台而言,一定要在保障产品质量的同时,努力提高在线评论信息获取的便捷度和内容的可信度,提高推荐参考价值,确保用户信息与财务安全,增强买家信任感;对买家而言,一定要提高在线评论信息分辨能力,合理挖掘买家在线评论所体现的信息,科学判断电商平台信誉度,并由此形成更为理性的消费,更好地保障自身权益;对监管机构而言,一定要切实发挥监督管理职能,协同电商和消费者营造良好购物环境,确保电子商务健康有序发展。
Buyer's online reviews are an important source of customers'trust,so it is of great significance to the analysis of the text of buyer's reviews.The authors study from the perspective of commentary factors and recommendation models.On the one hand,based on the mismatch between the three types of comments and the corresponding content of the comments,the authors propose the comment text centrality factor and the comment sentiment factor,consider the transaction time and the amount of money and other factors synthetically,introduce the feedback mechanism,and establish a more comprehensive and objective recommendation model.On the other hand,the model is simulated with algorithm programming.The model can effectively mine the real recommendation value of reviews,improve the reference value of the trust value to the buyer's decision-making,and has high reliability.The results show that in order to improve the buyer's trust,the online platform should not only ensure product quality,but also strive to improve the convenience and credibility of online review information.In addition,buyers'online reviews have an important impact on buyers'purchasing decisions.Buyers need to improve the resolution of online reviews information,thus forming a scientific shopping recommendation and rational shopping decisions.And the supervisors should play their role,create the sound shopping environment,and guarantee the sound order for the development of e-commerce.
作者
王兴芬
杜惠英
WANG Xing-fen;DU Hui-ying(Beijing Information Science&Technology University,Beijing100192,China)
出处
《中国流通经济》
CSSCI
北大核心
2018年第11期22-30,共9页
China Business and Market
基金
国家自然科学基金"网络零售交易风险动态评估及预警研究"(71571021)
北京市教委科技计划重点项目"电子商务平台交易纠纷规避的若干支撑技术研究"(KZ201411232036)
北京市教委科研计划项目"在线评论对C2C电子商务消费者购买决策的影响机制研究"(SM201511232004)
关键词
买家评论
文本中心度因子
情感因子
推荐信任
buyers’review
text centrality factor
sentiment factor
recommendation trust
