소셜 빅데이터 분석을 통한 포스트 코로나 시대 외식업계 동향:토픽모델 접근 (Food Industry Trends Post COVID-19 on Social Media:A Topic Model Analysis)

서지정보

· 발행기관 : (사)한국조리학회
· 수록지 정보 : Culinary Science & Hospitality Research / 28권 / 5호 / 104 ~ 113페이지
· 저자명 : 배소현, 김동진

초록

In this study, we explored keywords and latent topics related to food service industry during the COVID-19 pandemic by examining the posts on blogs, online forums, and news articles on Naver, Daum, and Google. In times of global crises such as the current COVID-19, it is useful to look into people’s honest opinions and thoughts, as well as traditional social research, that are timely offered through social networks. Key terms used for web crawling were “food industry” or “restaurant industry” from October 17, 2020 to October 17, 2021. After removing inaccurate and irrelevant words, we analyzed 9,338 online posts using TF-IDF values and topic modeling with latent Dirichlet allocation. Based on the results, five topics are identified: (1) consumer orientation, (2) coping with environmental change, (3) marketing by generation, (4) prices increase, and (5) ESG initiatives. This study contributes to the literature by revealing that COVID-19 has influenced on various domains of food service industry including health, safety, technology, delivery, employment, and environment using LDA topic modeling. In addition, operational contributions are provided according to the study results.

영어초록

In this study, we explored keywords and latent topics related to food service industry during the COVID-19 pandemic by examining the posts on blogs, online forums, and news articles on Naver, Daum, and Google. In times of global crises such as the current COVID-19, it is useful to look into people’s honest opinions and thoughts, as well as traditional social research, that are timely offered through social networks. Key terms used for web crawling were “food industry” or “restaurant industry” from October 17, 2020 to October 17, 2021. After removing inaccurate and irrelevant words, we analyzed 9,338 online posts using TF-IDF values and topic modeling with latent Dirichlet allocation. Based on the results, five topics are identified: (1) consumer orientation, (2) coping with environmental change, (3) marketing by generation, (4) prices increase, and (5) ESG initiatives. This study contributes to the literature by revealing that COVID-19 has influenced on various domains of food service industry including health, safety, technology, delivery, employment, and environment using LDA topic modeling. In addition, operational contributions are provided according to the study results.

참고자료

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