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Abstract
This study examined consumers’ emotions and needs related to dining-out experiences before and during the COVID-19 crisis. This study identifies words closely associated with the keyword “dining-out” based on big data gleaned from social media and investigates consumers’ perceptions of dining-out and related issues before and after COVID-19. The research findings can be summarized as follows: In 2019, frequently appearing dining-related words were dining-out, family, famous restaurant, recommend, and dinner. In 2020, they were dining-out, family, famous restaurant, and Corona. The analysis results for the dining-out sentimental network based on 2019 data revealed discourses revolving around delicious, nice, and easily. For the 2020 data, discourses revolved around struggling, and, cautious. The analysis of consumers’ dining-out demand network for 2019 data showed discourses centered around reservation, famous restaurant, meal, order, and coffee. However, for 2020 data, discourses were formed around delivery, price, order, take-out, and social distance. In short, with the outbreak of the pandemic, delivery, takeout, and social distance emerged as new search words. In addition, compared with before the COVID-19 pandemic, a weakening trend in positive emotions and an increasing trend in negative emotions were detected after the outbreak of the COVID-19 pandemic; specifically, fear was found to be the fear emotion.
Highlights
With technological advancement, network development, and the popularization of telecommunications, the volume of data has grown exponentially [1]
The present study examines consumers’ emotions and needs related to dining-out experiences before and after COVID-19 based on big data collected from social media
Narrative coding was done for text-mining indicators on dining-out and clustered into food, sentimental, demand/purpose, and tourism/region (Table 2)
Summary
Network development, and the popularization of telecommunications, the volume of data has grown exponentially [1]. Big data can be defined from the viewpoint of technology, size, and methodology. Big data indicates next-generation technology and architecture devised to collect, find, and analyze massive amounts of various data quickly [2]. Big data analysis looks at massive amounts of Internet-based data and is useful for identifying the meaning of information and their relationships [3]. With the advancement of the Internet and the popularization of related devices, people can communicate with each other at low costs on social network services (SNS), where they share experiences and thoughts, freely access social media, and connect with others [5]
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