Web celebrity shop assessment and improvement based on online review with probabilistic linguistic term sets by using se
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Web celebrity shop assessment and improvement based on online review with probabilistic linguistic term sets by using sentiment analysis and fuzzy cognitive map Decui Liang1 · Zhuoyin Dai1 · Mingwei Wang1 · Jinjun Li2
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract As a representative of the new economy, the web celebrity economy has achieved significant development in China with the rapid development of information technology and the Internet. In this environment, web celebrity shops encounter fierce business competition of peer competitors. Online reviews which imply the consumers’ attitudes and sentiments give the web celebrity shops good feedback to improve their competitiveness. Thus, taking milk tea as an example, this paper deeply investigates the assessment of web celebrity shops by mining online review. At the same time, we also discuss the competitive analysis and propose the corresponding improvement advices. In order to obtain the satisfaction assessments of web celebrity shops, on the one hand, we analyze topic extraction with latent dirichlet allocation (LDA) and determine the attributes that customers care about. On the other hand, we utilize long short-term memory (LSTM) and probabilistic linguistic term sets (PLTSs) to more precisely portray customers’ sentiment towards different attributes. By using fuzzy cognitive map (FCM) and the association rule, we further investigate the interrelationship among the attributes and construct the relationship graph between attributes for web celebrity
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Decui Liang [email protected] Zhuoyin Dai [email protected] Mingwei Wang [email protected] Jinjun Li [email protected]
1
School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
2
School of Economics and Management, Sichuan Tourism University, Chengdu 610100, Sichuan, China
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D. Liang et al.
shops. With the above results, we aggregate the decision information by designing improved extended Bonferroni mean (EBM) and obtain comprehensive evaluations. General speaking, this paper successfully transforms the unstructured data of online reviews into quantitative information and obtain satisfaction evaluations. With the aid of PLTSs and FCM, we further investigate the competitive analysis and propose improvement advices for each shop, which systematically provides us with a datadriven decision-making analysis model. Keywords Online review · Fuzzy cognitive map · Sentiment analysis · Web celebrity shop assessment · Probabilistic linguistic term sets
1 Introduction Web celebrity economy refers to a new economic mode that relies on the Internet, especially mobile Internet communication and its social platform promotion. With the development of the Internet economy, the mode gathers much social attention, holds a vast fan base and targeted marketing market, generates various consumer markets around web celebrity intellectual property (IP), and forms a complete web celebrity industrial chain Guan and Wu (2016). With t
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