关键词: 旅游交通, 满意度, 大数据, 地理探测器, 空间分异

Abstract: The unique nature of tourism activities determines that tourism cannot leave traffic alone, especially urban tourism, and the choice of more ways of transportation makes it possible for urban self-help tourism. Tourism traffic is also important for the sustainable development of urban tourism. Satisfaction of tourism traffic is an important factor to determine the overall satisfaction of the destination, and can significantly affect the willingness of tourists to revisit. Investigation and research to that can guide the construction and improvement of urban tourism traffic, and promote the development of urban tourism. Compared with the traditional questionnaire data, the use of large tourist data to study tourist traffic satisfaction can solve the problems of small research area and inaccurate sampling of data. This method can reflect the satisfaction of tourism traffic in a large area, and the difference in the small area, which is of great significance for the planning and development of tourism traffic. This paper, through the screening of the captured network tourism reviews, uses text analysis techniques such as word matching and emotion discrimination to judge the emotional tendency of each comment, and constructs the emotional index of each city to represent its non-negative rating through the model, which is the tourist satisfaction. Finally, we use geodetector and correlation analysis to explore the spatial differentiation of urban tourism traffic satisfaction and the mechanism that influences its differentiation. The research shows that: 1) The tourist satisfaction degree of urban tourism traffic in mainland China has little difference in the region, and the difference is significant between provinces and cities. 2) The spatial difference of urban tourism traffic evaluation is mainly affected by the level of transport development. 3) There is a negative correlation between urban tourism traffic satisfaction and urban congestion index, and there is a positive correlation with urban road density, and there is no significant correlation with the factors such as the subway and the civil aviation airport. Therefore, due to the impact of urban traffic congestion, the traffic satisfaction of big cities and megacities is not high. 4) According to the satisfaction of urban tourism traffic and the level of traffic development, the national cities are divided into 4 categories: the A category is double index medium level Balanced Development Zone, the B category is double index low level Balanced Development Zone, the C category is the priority development zone of tourist traffic satisfaction, and the D category is the lagging development zone of tourist traffic satisfaction.

Key words: tourist traffic, satisfaction, tourism big data, Geodetector, spatial differentiation