Research on the Differentiation of Tourist Flow Network of Different Tourist Attractions in the Region

Abstract

Tourist flow research is an important part of tourism research, providing the basis for the development of tourism. This paper takes different scenic spots in nine regions of M as the research object, takes social network analysis as the primary research method, and evaluates the node and overall network structure characteristics of tourist flow in M through the social node and overall network structure indicators. Using the “Octopus Collector” software to collect data, integrating 685 online travelogues about this region on the platform of related tourism websites, and using related software to process and analyze the data, it is found that there is a great deal of variability between different tourist attractions in M. From the viewpoint of node network structure, M1 scenic spot is in the center position between M tourist attractions, and among the 38 different scenic spots investigated in M area, there are only 6 attractions with extremely strong competitiveness, which can play the role of guiding the flow direction of tourist streams, and the others basically rely on the driving of the tourist volume of these tourist nodes in order to develop. From the overall network structure, the outward value, inward value, outward value and inward value close to the center potential of the degree center potential in the tourist flow network of M is greater than 30%, the overall scenic nodes of M are not closely connected, and the difference between the core scenic spots and the marginal scenic spots in terms of tourist flow is large.