Awareness of manipulation in on-line review

Ching-Yun Hsueh, Long-Sheng Chen, Qiangfu Zhao
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引用次数: 0

Abstract

With the proliferation of e-commerce, internet has become an excellent platform for gathering and sharing consumers' personal views on, preferences for, and experiences with products. With the popularity of text based communication tools, customers can easily express their opinions about purchased products or services. Generally speaking, the on-line reviews should be unbiased reflections of the consumers' experiences with the products or services. However, some comments are biased "manipulation", which might reduce consumers' purchase intentions and bring a great damage to enterprisers. Although the existence of manipulation has been assumed widely, there are few results available in the literature for manipulation detection. This study aims to improve the performance for manipulation detection through feature selection. The study is divided into three parts. In the first part, we use conventional feature vectors obtained directly from the text files, and show that these feature vectors are in fact not useful for manipulation detection. In the second part, we adopt eight features recommended in the literature, and show that these features can improve the detection rate significantly. In the third part, we add three new features that can improve the detection accuracy further. A real case study of smart phone is used to illustrate the effectiveness of the proposed features.
意识到在线评论中的操纵
随着电子商务的蓬勃发展,互联网已成为消费者收集和分享个人对产品的看法、偏好和体验的绝佳平台。随着基于文本的交流工具的普及,顾客可以很容易地表达他们对购买的产品或服务的意见。一般来说,在线评论应该是消费者对产品或服务体验的客观反映。然而,有些评论带有“操纵”的偏见,这可能会降低消费者的购买意愿,给企业家带来很大的伤害。尽管操纵的存在已被广泛假设,但在文献中很少有关于操纵检测的结果。本研究旨在通过特征选择来提高操作检测的性能。本研究分为三个部分。在第一部分中,我们使用直接从文本文件中获得的常规特征向量,并表明这些特征向量实际上对操作检测没有用处。在第二部分中,我们采用了文献中推荐的八个特征,并表明这些特征可以显著提高检测率。在第三部分,我们增加了三个新的特征,可以进一步提高检测精度。一个真实的智能手机案例研究被用来说明所提出的功能的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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