School of Information Technology, Hunan University of Finance and Economics, Changsha 410205, China.
School of Information Management, Jiangxi University of Finance and Economics, Nanchang 330013, China.
J Healthc Eng. 2021 Oct 19;2021:7475022. doi: 10.1155/2021/7475022. eCollection 2021.
Online deceptive reviews widely exist in the online shopping environment. Numerous studies have investigated the impact of online product reviews on customer behaviour and sales. However, the existing literature is mainly based on real product reviews; only a few studies have investigated deceptive reviews. Based on the results of deceptive reviews, this article explores the factors that affect customer purchase decision in online review systems, which is flooded by deceptive reviews. Therefore, a deceptive review influence model is proposed based on three influential factors of online review system, sentiment characteristics, review length, and online seller characteristics. Based on them, text mining is used to quantify the indicators of the three influential factors. Through principal component analysis and linear regression, the experimental results of electronic appliances on Tmall show that the three influential factors are positively related to customers' purchase intention and decision making.
在线虚假评论在网络购物环境中广泛存在。许多研究都考察了在线产品评论对顾客行为和销售的影响。然而，现有文献主要基于真实产品评论，只有少数研究涉及虚假评论。本文基于虚假评论的结果，探讨了在充斥着虚假评论的在线评论系统中，影响顾客购买决策的因素。因此，提出了一个基于在线评论系统的三个影响因素、情感特征、评论长度和在线卖家特征的虚假评论影响模型。在此基础上，利用文本挖掘技术对三个影响因素的指标进行量化。通过主成分分析和线性回归，对天猫上的电子产品进行实验，结果表明这三个影响因素与顾客的购买意愿和决策呈正相关关系。
