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Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry

Author

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  • Wen-Kuo Chen

    (Department of Marketing and Logistics Management, Chaoyang University of Technology, Taichung 413310, Taiwan)

  • Dalianus Riantama

    (Department of Business Administration, Chaoyang University of Technology, Taichung 413310, Taiwan
    College of Management, Dayeh University, Changhua 515006, Taiwan)

  • Long-Sheng Chen

    (Department of Information Management, Chaoyang University of Technology, Taichung 413310, Taiwan)

Abstract

Due to the COVID-19 pandemic, the sales of fast-food businesses have dropped sharply. Customer satisfaction has always been one of the key factors for the sustainable development of enterprises. However, in the fast-food restaurant business, gaining the knowledge of customer satisfaction is one of the critical tasks. Moreover, text reviews in social media have become one of important reference sources for customers’ decisions in buying services and products. Therefore, the main purpose of this study is to explore whether customer voices from social media reviews are different during the COVID-19 outbreak and to propose a new method to reduce interpersonal contact when collecting data. A text mining scheme which includes least absolute shrinkage and selection operator (LASSO) and decision trees (DT) are presented to discover the essential factors for customers to increase their satisfaction from unstructured online customer reviews. Finally, three real world review sets were employed to validate the effectiveness of the presented text mining scheme. Experimental results can help companies to properly adapt to similar epidemic situations in the future and facilitate their sustainable development.

Suggested Citation

  • Wen-Kuo Chen & Dalianus Riantama & Long-Sheng Chen, 2020. "Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2020:i:1:p:268-:d:470496
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    1. Sezgen, Eren & Mason, Keith J. & Mayer, Robert, 2019. "Voice of airline passenger: A text mining approach to understand customer satisfaction," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 65-74.
    2. Brown, Alasdair & Reade, J. James, 2019. "The wisdom of amateur crowds: Evidence from an online community of sports tipsters," European Journal of Operational Research, Elsevier, vol. 272(3), pages 1073-1081.
    3. Bommert, Andrea & Sun, Xudong & Bischl, Bernd & Rahnenführer, Jörg & Lang, Michel, 2020. "Benchmark for filter methods for feature selection in high-dimensional classification data," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    4. Kim, Kun & Park, Oun-joung & Yun, Seunghyun & Yun, Haejung, 2017. "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 362-369.
    5. Cuiqing Jiang & Yao Liu & Yong Ding & Kun Liang & Rui Duan, 2017. "Capturing helpful reviews from social media for product quality improvement: a multi-class classification approach," International Journal of Production Research, Taylor & Francis Journals, vol. 55(12), pages 3528-3541, June.
    6. Liu, Zhiwei & Park, Sangwon, 2015. "What makes a useful online review? Implication for travel product websites," Tourism Management, Elsevier, vol. 47(C), pages 140-151.
    7. Gao, Baojun & Li, Xiangge & Liu, Shan & Fang, Debin, 2018. "How power distance affects online hotel ratings: The positive moderating roles of hotel chain and reviewers’ travel experience," Tourism Management, Elsevier, vol. 65(C), pages 176-186.
    8. Aron Culotta & Jennifer Cutler, 2016. "Mining Brand Perceptions from Twitter Social Networks," Marketing Science, INFORMS, vol. 35(3), pages 343-362, May.
    9. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    10. Jian-Wu Bi & Yang Liu & Zhi-Ping Fan & Erik Cambria, 2019. "Modelling customer satisfaction from online reviews using ensemble neural network and effect-based Kano model," International Journal of Production Research, Taylor & Francis Journals, vol. 57(22), pages 7068-7088, November.
    11. Godnov, Uroš & Redek, Tjaša, 2016. "Application of text mining in tourism: Case of Croatia," Annals of Tourism Research, Elsevier, vol. 58(C), pages 162-166.
    12. Sant’Anna, Leonardo Riegel & Caldeira, João Frois & Filomena, Tiago Pascoal, 2020. "Lasso-based index tracking and statistical arbitrage long-short strategies," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    13. Amaro, Suzanne & Duarte, Paulo & Henriques, Carla, 2016. "Travelers’ use of social media: A clustering approach," Annals of Tourism Research, Elsevier, vol. 59(C), pages 1-15.
    14. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
    15. Tian, Shaonan & Yu, Yan & Guo, Hui, 2015. "Variable selection and corporate bankruptcy forecasts," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 89-100.
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