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Research on Filter Model of Customer Review for Sentiment Analysis |
Cai Xiaozhen1, Xu Jian1, Wu Sizhu2 |
1. School of Information Management, Sun Yat-Sen University, Guangzhou 510006, China;
2. Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China |
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Abstract [Objective] Aiming at the problem of quality testing in the process of sentiment analysis research, the paper constructs a filter model to select more suitable review. [Methods] It selects four indexes namely product words, length of review, emotional strength and adjunct words as judgment references, using multiple linear regression method and data from shopping website to construct the model. [Results] The four indexes are related to the quality of review, and the filter model gains high accuracy in terms of recall rate and precision so that it provides a new method for selection of data source in the sentiment analysis research. [Limitations] Data scarcityleads to the limitation ofthe filter model. [Conclusions] The model can judge the quality of customer reviews in the range of permitted errors.
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Received: 24 December 2013
Published: 19 May 2014
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[1] Liu Y,Huang X J.Modeling and Predicting the Helpfulness of Online Reviews[C].In:Proceedings of the 8th IEEE International Conference on Data Mining.2008:443-452.
[2] 郝媛媛,叶强,李一军.基于影评数据的在线评论有用性影响因素研究[J].管理科学学报,2010,13(8):78-88,96.(Hao Yuanyuan,Ye Qiang,Li Yijun.Research on Online Impact Factors of Customer Review Usefulness Based on Movie Reviews Data[J].Journal of Management Sciences in China,2010,13(8):78-88,96.)
[3] Mudambi S M,Schuff D.What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com[J].MIS Quarterly,2010,34 (1):185-200.
[4] Chen C C,Tseng Y D.Quality Evaluation of Product Reviews Using an Information Quality Framework[J].Decision Support Systems,2011,50(4) :755-768.
[5] 孙升芸,田萱.产品垃圾评论检测研究综述[J].计算机科学,2011,38(10A):198-201.(Sun Shengyun,Tian Xuan.Survey on Product Review Spam Detection[J].Computer Science,2011,38(10A):198-201.)
[6] 刘送英.在线顾客评论有用性研究[D].厦门:华侨大学,2011.(Liu Songying.Survey on the Usefulness of Online Customer Reviews[D].Xiamen :HuaQiao University,2011.)
[7] 苏雪佳.B2C在线评论有用性影响因素研究——以亚马逊网站为例[D].武汉:中南民族大学,2012.(Su Xuejia.A Study of the Impact Factors of the Helpfulness of B2C Online Reviews —— A Case Study of Amazon[D].Wuhan:South- Central University for Nationalities,2012.)
[8] 姜巍,张莉,戴翼,等.面向用户需求获取的在线评论有用性分析[J].计算机学报,2013,36(1):119-130.(Jiang Wei,Zhang Li,Dai Yi,et al.Analyzing Helpfulness of Online Reviews for Users Requirements Elicitation[J] .Chinese Journal of Computers,2013,36 (1) :119-130.)
[9] 朱玉洁.商业银行在线评论的影响研究[J].商品与质量,2011(S):177-178.(Zhu Yujie .Survey on the Impact of Online Reviews of Business Bank[J].Goods and Quality,2011(S):177-178.)
[10] Amazon[EB/OL].[2013-09-09].http://www.amazon.cn/.
[11] 京东商城[EB/OL].[2014-01-03].http://www.jd.com/.(JD Online Shopping Mall[EB/OL].[2014-01-03].http://www.jd.com/.)
[12] Wikipedia.SPSS[EB/OL].[2013-10-08].http://zh.wikipedia.org/wiki/SPSS.
[13] Wikipedia.Spearman's Rank Correlation Coefficient[EB/OL].[2013-10-08].http://en.wikipedia.org/wiki/Spearman%27s_ rank_correlation_coefficient.
[14] Wikipedia.文本信息检索[EB/OL].[2014-01-21].http://zh.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E4%BF%A1%E6%81%AF%E6%A3%80%E7%B4%A2.(Wikipedia.Document retrieval[EB/OL].[2014-01-21].http://zh.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E4%BF%A1%E6%81%AF%E6%A3%80%E7%B4%A2.) |
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