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

Wen-Kuo Chen, Dalianus Riantama and Long-Sheng Chen
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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
Long-Sheng Chen: Department of Information Management, Chaoyang University of Technology, Taichung 413310, Taiwan

Sustainability, 2020, vol. 13, issue 1, 1-17

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.

Keywords: online customer reviews; text mining; customer satisfaction; feature selection (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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