论文标题

积极的情绪有助于对电子商务的负面评论进行排名

Positive emotions help rank negative reviews in e-commerce

论文作者

Weng, Di, Zhao, Jichang

论文摘要

负面评论,后购买评估的评级不佳,在电子商务中起着必不可少的作用,尤其是在塑造未来的销售和公司股票方面。但是,现有的研究很少研究其对卖方和生产商的潜在价值,以增强提供更好的服务和产品的能力。对于那些在电子商务守护者那里利用评论有益的人来说,为客户开发了排名方法。为了填补这一空白,就描述文本和情感极性结合起来,本研究中排名方法的目的是为在线卖家和生产商提供某些产品属性下的最有用的负面评论。通过应用更合理的评估程序,雇用了具有相关背景的专家来投票给排名方法。我们的排名方法对于对卖方和生产商的负面评价进行排名更可靠,表现出比BM25这样的基准的表现更好,结果高8%。在本文中,我们还丰富了以前对情感的理解,以评估评论。具体而言,令人惊讶的是,积极情绪在排名负面评论方面更有帮助,而不是负面情绪。排名中积极情绪的意外增强表明,对负面经验的两极分化评论实际上提供了更多理性的反馈,从而对卖方和生产者提供了更多的帮助。提出的排名方法可以为电子商务从业人员提供一种有效的有效方法,以利用在线消费者的负面评论。

Negative reviews, the poor ratings in postpurchase evaluation, play an indispensable role in e-commerce, especially in shaping future sales and firm equities. However, extant studies seldom examine their potential value for sellers and producers in enhancing capabilities of providing better services and products. For those who exploited the helpfulness of reviews in the view of e-commerce keepers, the ranking approaches were developed for customers instead. To fill this gap, in terms of combining description texts and emotion polarities, the aim of the ranking method in this study is to provide the most helpful negative reviews under a certain product attribute for online sellers and producers. By applying a more reasonable evaluating procedure, experts with related backgrounds are hired to vote for the ranking approaches. Our ranking method turns out to be more reliable for ranking negative reviews for sellers and producers, demonstrating a better performance than the baselines like BM25 with a result of 8% higher. In this paper, we also enrich the previous understandings of emotions in valuing reviews. Specifically, it is surprisingly found that positive emotions are more helpful rather than negative emotions in ranking negative reviews. The unexpected strengthening from positive emotions in ranking suggests that less polarized reviews on negative experience in fact offer more rational feedbacks and thus more helpfulness to the sellers and producers. The presented ranking method could provide e-commerce practitioners with an efficient and effective way to leverage negative reviews from online consumers.

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