电子商务说服性推荐评论读者群分析的概念层次方法

Nur Syadhila Bt Che Lah, Ab Razak Che Hussin, H. M. Dahlan
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引用次数: 5

摘要

电子商务平台的快速发展使得零售商能够引入在线产品推荐来说服消费者做出购买决定。电子商务中的推荐系统可以通过开发意见审查或反馈系统来实现。意见评论作为一种有说服力的沟通工具,其可见性在购买过程中起着重要的作用,近年来引起了研究学者的广泛关注。为了扩展目前关于在线评论系统说服潜力的讨论,本文旨在探讨文本信息的质量如何影响在线推荐的说服力。在分析文本可读性的过程中,将采用概念层面的方法,以产生有说服力的交际信息。提出了一种基于概念评论数对观点评论读者群及其说服特征的评论长度影响的理论模型。为了验证该模型的有效性,我们应用Gunning-Fox指数(FOG)的基本可读性度量来检验意见评论的可读性难易程度,该数据集包含从Amazon.com产品评论中提取的1054条评论。本文进一步探讨了概念层次分析、评论读者群和说服性评论之间的相互关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A concept-level approach in analyzing review readership for E-Commerce persuasive recommendation
A rapid development of E-Commerce platforms has allowed retailers to introduce online product recommendations to persuade consumers purchase decisions. Recommendations system in E-Commerce can be implemented through development of opinion review or feedback system. The visibility of opinion review as a persuasive communication tool in recommendation context has been proven as an important role in purchasing process, which then triggers much attention recently among research scholars. To expand the current discussion on persuasive potential of online review system, this paper aims to explore how the quality of text message may affects the persuasiveness of online recommendation. A concept-level approach will be used in analyzing text readability ease towards generating persuasive communication message. A theoretical model is proposed to measure the effect of review length based on number of concept review towards opinion review readership and its persuasive features. In order to validate the model, we applied basic readability measure of Gunning-Fox Index (FOG) to examine readability ease of opinion review to a dataset containing 1054 reviews extracted from Amazon.com product review. The interrelationship between concept-level analysis, review readership and its persuasive review is further discussed in this paper.
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