Abstract
The purpose of this study is to investigate the difference in online reviews of hotels before and after COVID-19. To achieve the research purpose, data were collected and analyzed through engineering skills such as web crawling and text mining. Target data are categorized into two periods based on the COVID-19 pandemic declaration date (March 12, 2020), before COVID-19 (January 1, 2018 -March 11, 2020) and after COVID-19 (March 12, 2020 - June 22, 2022). Online review data were collected from 20 hotels (5-stars level) in Seoul, South Korea. Results from the analysis of review data is summarized as follows: 1) the frequency of keywords, 2) the analysis of semantic network analysis and 3) the sentiment analysis for both positive comments and negative comments both before and after COVID-19 showed that customers are likely to be more sensitive to public facilities and location of hotels for before COVID-19, but they are likely to be more sensitive on the crowded environment at the lobby and waiting time for check-in and check-out. Based on the result, service enhancement strategies for domestic hotels are suggested.
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