KEYWORDS: Mining, Spatial analysis, Analytical research, Visualization, Internet, Visual analytics, Probability theory, Data modeling, Web 2.0 technologies, Social networks
After the outbreak of COVID in Wuhan, it has had an impact on all aspects of tourism industry. Tourists' sentiment is an important factor for people to make tourism decisions. The implementation of tourism decisions affects the development of tourism to a certain extent. In order to explore the impact of the COVID-19 on the tourism industry from the micro level of tourist sentiment. Firstly, the text mining algorithm is used to analyze the emotion of tourism microblog text, and the tourism emotion index TSI is constructed. Then combined with the tourism heat index THI, the tourist sentiment TS comprehensive index is constructed. The temporal and spatial differences of the impact of the epidemic on tourists' emotion are analyzed by comparing the tourists' emotion and epidemic data in different regions and stages. From the temporal and spatial distribution of tourist sentiment and epidemic situation, they are not completely parallel related, and there is spatial heterogeneity. Tourist sentiment is affected by multiple factors such as economic level and geographical location. The change of tourists' mood does not only depend on the change of epidemic data, but also related to many factors such as economic level and geographical location.
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