Clause-level Analysis High-value Reviews based on Sentiment

J. Data Intell. Pub Date : 2020-12-01 DOI:10.26421/JDI1.4-4
Akiyo Nadamoto, Kazuhiro Akiyama, T. Kumamoto
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Abstract

Today, huge numbers of reviews are posted on the internet. Online shoppers often refer to reviews written about the products. A review has a star rating that represents what other people think about the product. However, the star rating is not always appropriate for evaluating the product. High-value reviews that affect the users' willingness to buy are independent of the number of stars in ratings. High-value reviews are those from which people find useful information those regarded as good reviews. As described in this paper, we investigated the relation between high-value reviews and the sentiment (positive/negative/neutral) of their clauses based on four hypotheses. We extract characteristics of high-value reviews based on our results. Furthermore, we propose a classification method that classifies clause level sentiment from reviews.
基于情感的高价值评论的子句分析
今天,互联网上发布了大量的评论。网上购物者通常会参考有关产品的评论。一篇评论有一个星级,代表了其他人对产品的看法。然而,星级评级并不总是适合于评估产品。影响用户购买意愿的高价值评论与评级中的星级数无关。高价值评论是人们从中找到有用信息的那些被认为是好的评论。如本文所述,我们在四个假设的基础上研究了高价值评论与其子句情绪(积极/消极/中性)之间的关系。我们根据我们的结果提取高价值评论的特征。此外,我们提出了一种从评论中分类子句级情感的分类方法。
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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