Rural tourism, as an important part of the tourism service industry, the study of the spatio-temporal evolution and influence mechanism of rural tourism flow has also become a hot topic at present. This paper takes Jiangsu Province of China as the research area, proposes the heat measurement and identification method of rural tourism based on network data, constructs a heat measurement model, takes standard deviation ellipse analysis, average nearest neighbor index method, kernel density analysis as the core method of spatial analysis, and proposes the hotspot identification method on the demand of spatial relevance analysis, so as to provide the method and means for the analysis of the spatio-temporal evolution of the rural tourism flow. In the analysis of the influence mechanism of rural tourism flow, the QAP model is used as a research tool to explore the influencing factors of rural tourism flow.The value of rural tourism hotness was low during 2014-2017, and it has rapidly increased and maintained a high growth trend since 2018. The Gini coefficient of rural tourism hotness increased from 0.51 in 2014 to 0.72 in 2018, and then fell back to 0.65 in 2023, and the degree of spatial difference of rural tourism hotness showed a weakening trend, and the hotspot areas of rural tourism were increasing. The structure of tourism flow is affected by a variety of factors such as spatial proximity, tourism income, and the impacts produced by the factors change somewhat in different time periods.