[Objective] We explore the changing of consumer’s favorite brands by analyzing online product reviews from a popular E-commerce platform in China. [Methods] First, we built a fuzzy sentiment dictionary for online product reviews based on brand switching intention model. Second, we defined rules for a Fuzzy Inference System to calculate customer brand switching intention and switching types. [Results] We successfully extracted vague sentimental terms from the online product reviews, and then categorized consumers’ intentions. [Limitations] The fuzzy sentiment dictionary was built with complex rules and required many time consuming follow-up amendments. [Conclusions] The proposed model can provide decisive information for online marketing and early warning systems.
张艳丰,李贺,彭丽徽. 基于模糊情感计算的商品在线评论用户品牌转换意向研究*[J]. 现代图书情报技术, 2016, 32(5): 64-71.
Zhang Yanfeng,Li He,Peng Lihui. Research on the Brand Switching Intention of Online Product Reviews Based on the Fuzzy Sentiment Calculation. New Technology of Library and Information Service, 2016, 32(5): 64-71.
(CNNIC. Research Report on China’s Online Shopping Market in 2014 [EB/OL]. [2015-09-16].
[2]
Utz S, Kerkhof P, Van Den Bos J. Consumers Rule: How Consumer Reviews Influence Perceived Trustworthiness of Online Stores[J]. Electronic Commerce Research and Applications, 2012, 11(1): 49-58.
(Zeng Runxi, Wang Junze, Du Hongtao.Research on Opinion Extraction Mechanism of Web Information Reviews in New Media Times[J]. Library and Information Service, 2015, 59(14): 111-116, 148.)
[4]
Dellarocas C, Zhang X, Awad N F.Exploring the Value of Online Product Reviews in Forecasting Sales: The Case of Motion Pictures[J]. Journal of Interactive Marketing, 2007, 21(4): 23-45.
[5]
Rose S, Clark M, Samouel P, et al.Online Customer Experience in E-Retailing: An Empirical Model of Antecedents and Outcomes[J]. Journal of Retailing, 2012, 88(2): 308-322.
(Qian Ying,Wang Xizi,Ni Junyu.Review of Research on the Role of Switching Costs in Loyalty of Online Users[J]. Journal of Intelligence, 2015, 34(3): 203-207.)
[7]
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.
(Hao Yuanyuan, Ye Qiang, Li Yijun.Research on Online Impact Factors of Customer Reviews Usefulness Based on Movie Reviews Data[J]. Journal of Management Sciences in China, 2010, 13(8): 78-88, 96.)
(Zhao Narisa, Li Yuan.Online-Review-Based Fuzzy Computing and Inference of Consumer Sentiment[J]. Journal of the China Society for Scientific and Technical Information, 2011, 30(4): 412-423.)
(Song Shuang, Zhao Narisa, Zhang Yang.Approximate Reasoning Research of Customers Brand Switching Intention Based on Online Reviews[J]. Journal of Shandong University: Natural Science, 2014, 49(12): 7-11.)
[11]
Bhattacherjee A, Perols J, Sanford C.Information Technology Continuance: A Theoretic Extension and Empirical Test[J]. Journal of Computer Information Systems, 2008, 49(1): 17-26.
[12]
HowNet [EB/OL]. [2015-11-10]. .
[13]
数据堂. 台湾大学NTUSD-简体中文情感极性词典[EB/OL]. [2015-11-11]. .
[13]
(Data Tang. Taiwan University-The Polarity of Simplified Chinese Emotional Dictionary [EB/OL]. [2015-11-11].
(Dong Lili, Zhao Fanrong, Zhang Xiang.Analysing Propensity of Product Reviews Based on Domain Ontology and Sentiment Lexicon[J]. Computer Applications and Software, 2014, 31(12): 104-108, 194.)
(Lou Decheng, Yao Tianfang.Semantic Polarity Analysis and Opinion Mining on Chinese Review Sentences[J]. Computer Applications, 2006, 26(11): 2622-2625.)
[16]
LTP-Cloud.语言技术平台云[EB/OL]. [2015-11-21]. .
[16]
(LTP-Cloud. Language Technology Platform Cloud [EB/OL]. [2015-11-21].
(He Yue, Song Lingxi, Qi Liyun.Spillover Effect of Internet Word of Mouth in Negative Events——Take the “Deadly Yuantong Express” Event for an Example[J]. New Technology of Library and Information Service, 2015(10): 58-64.)
[18]
Ganesh J, Arnold M J, Reynolds K E.Understanding the Customer Base of Service Providers: An Examination of the Differences Between Switchers and Stayers[J]. Journal of Marketing, 2000, 64(3): 65-87.
(Cai Xiaozhen, Xu Jian, Wu Sizhu.Research on Filter Model of Customer Review for Sentiment Analysis[J]. New Technology of Library and Information Service, 2014(4): 58-64.)