Abstract: in this article, search query data of tourism element of 24 major cities in China is used, and processes and technical methods are established for keywords of tourism elements selecting, search query data mining and stripping. Entropy method is used to integrate comprehensive index of search query data to analyze network attention-degree of the cities. Combined with Coefficient of Variation, Herfindahl index, and standard deviation ellipse method, the evolution of the spatial pattern of urban tourism elements be explored from 2011 to 2015. This article draws a conclusion that ‘Meals, lodging, travel, shopping, tour, and entertainment’ have different degrees of attractiveness. Coefficient of Variation of ‘Meals, lodging, travel, entertainment’ shows fluctuation of “V” shape. Shopping’s is getting larger and larger, but tour’s is getting smaller and smaller. Although the evolution of the spatial pattern has some similarities, the standard deviation ellipse which be acquired by using the search query data of ‘Meals, lodging, travel, shopping’ offset towards southwest, and of ‘travel, entertainment’ is showing a shift northeast.