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Chinese railway has entered the "HSR era", while the structure of "four vertical and four horizontal" railways for transit passengers is almost completed. Taking the Beijing-Shanghai High-Speed Rail(hereinafter referred to as HSR) as an example, this paper first explores HSR’s effects on the spatial structure of regional tourist flows using the social network analysis. Next, it notes changes in the accessibility of regional transportation. After analyzing the factors including initial endowment of regional tourism resources, hospitality facilities, the density of the regional tourism transportation network, and locations, the paper discusses the mechanisms through which HSR affects regional tourist flows. The study shows the following:(1) HSR’s effects on the spatial structure of regional tourist flows are manifested through the Matthew effect, the filtering effect, the diffusion effect and the overlying effect, and(2) the Matthew effect of HSR is manifested under an obvious interaction of the location, the initial endowment of tourism resources, hospitality capacity, tourist transportation network density and "time-space compression". The filtering effect of HSR is manifested for those tourism nodes without favorable location conditions, endowment of tourism resources, hospitality capacity, or tourist transportation network density and without obvious benefits from "time-space compression". Those tourism nodes that boast advantages in terms of location condition, endowment of tourism resources, hospitality capacity, tourist transportation network density and obvious "time-space compression" will become sources for the diffusion effect. HSR will strengthen the aggregation effects of tourist flow in these diffusion sources, which will thereafter diffuse to peripheral tourist areas, manifesting "aggregation-diffusion". HSR has overlapped tourists’ spatial traveling range over large-scale spaces. However, the overlying effect is only generated in those tourism nodes with a favorable location condition, an endowment of tourism resources, hospitality capacity, tourist transportation network density, and obvious "time-space compression".