Tourism index is a "barometer" to reflect the overall development level of tourism.The tourism index compiled by historical data can not reflect the real situation accurately with the increasing influence of network events on tourism In the Internet era.This study collects time series data of tourism network search by Baidu index tool and Accessory uses data mining method and principal component analysis method to detect and standardize the stability of the data.The spss system and the weighted analysis method TEA TREE OIL SOAP are used to construct the tourism network index model.
Finally, the model detection is carried out by comparing the actual tourism data in Sanya.This study is an important supplement to the existing tourism index.