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18 March 2022 Spatio-temporal analysis of network attention of tourist destinations under epidemic situation of novel coronavirus: based on Guilin's Baidu index analysis
Shixing Qiu, Fuxing Liang, Kaiyong Chen
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Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121682W (2022) https://doi.org/10.1117/12.2631309
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China
Abstract
Tourism has become one of China's important economic pillar industries, and the revitalization of the tourism industry in the context of the COVID-19 epidemic is an issue worthy of attention. This article will take Guilin network attention as the research object, Baidu index data as the data source, seasonal concentration index and geographic concentration index as the research methods, and use Python software to visualize Baidu index data. Through the visualization of the monthly, weekly and geographic spatial distribution of the data, it can be seen that: 1. Guilin's network attention under the background of the COVID-19 epidemic is sluggish; 2. Guilin's annual tourism network attention has seasonal time concentration and geographic spatial distribution. This is to predict the situation of tourism demand during the post-epidemic period in Guilin in the future, and to prepare for the recovery of tourism after the epidemic in Guilin.
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Shixing Qiu, Fuxing Liang, and Kaiyong Chen "Spatio-temporal analysis of network attention of tourist destinations under epidemic situation of novel coronavirus: based on Guilin's Baidu index analysis", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121682W (18 March 2022); https://doi.org/10.1117/12.2631309
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KEYWORDS
Internet
Analytical research
Visualization
Data analysis
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