有意义文本分析在在线产品评论中的应用

2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) Pub Date : 2018-09-01 DOI:10.1109/SYNASC.2018.00057

C. Bǎdicǎ, Georgian Vladutu

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引用次数: 3

摘要

在线评论对意见分享有显著影响，因此在购买过程中起着重要作用。本文研究了在线评论评分分数和有用性与可读性测试所测量的属性之间的关系。此外，我们调查了用户之间的交互，根据我们的数据集，我们发现大多数交互是在客户和产品所有者之间进行的。最后，我们提出了一种评论情感分析算法，并利用评论评级分数对其进行了实验评估。

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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Application of Meaningful Text Analytics to Online Product Reviews

Online reviews have a significant impact on opinion sharing, thus playing an important role in the purchase process. In this paper we examine the relations between the online review rating score and helpfulness on one hand and attributes measured by the readability tests on the other hand. Furthermore we investigated the interaction between users and, based on our data sets, we found that most of these are between customers and product owners. Lastly we proposed a sentiment analysis algorithm of reviews and we experimentally evaluated it using the review rating scores.

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2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

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