A Correlation Coupling Prediction of Island Tourist Based on Multi Key Words of Web Search Index: A Case Study of Gulang Island in Xiamen

He, Y.; Huang, L.Y.; Ding, C.; Zou, Y., and Huang, P., 2020. A correlation coupling prediction of island tourist based on multi key words of web search index: A case study of Gulang Island in Xiamen. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 373-378. Coconut Creek (Florida), ISSN 0749-0208.With the rapid rise of the Internet, people rely more on the Internet to collect tourism information when traveling. This paper will make a model by Baidu search index of keywords in scenic spot, use weighted calculation and composite index, take Gulang island in Xiamen as an example to verify the feasibility of the model, and conduct heat prediction analysis of scenic spot through prediction model. Through analysis and research, it is found that the Baidu search index has a strong positive correlation with the tourist volume of scenic spots, and the tourist volume and popularity of scenic spots can be predicted by the search volume of Baidu. This conclusion is conducive to the coordination and control between the government and the scenic spots, the market analysis of tourism enterprises, and the tourists' comfortable experience of peak travel.