Spatial network of urban tourist flow in Xi’an based on microblog big data

Abstract

ABSTRACTThe mobile internet and social media have changed people’s travel behavior. During a journey, tourists generate a large amount of ‘digital footprint’ that can be used for studying tourist behavior. Exploring tourist spatial behavior based on social media big data is a new research field. Using the example of Xi’an, this study attempts to reveal the characteristics of tourists’ spatial network of tourist flow behavior rules and the function of travel areas and nodes by analyzing the spatial network of tourist flow using social network analysis and data visualization based on microblog-geotagged big data generated by tourists. Geotagged messages are obtained from the Open API of the Sina Microblog. This study found that tourism development shows characteristic of spatial aggregation. The Bell Tower, Qujiang, and Lintong areas are the most crucial tourism development areas in Xi’an. Furthermore, there are obvious hierarchical characteristics in a tourism spatial network. Travel nodes can be divided into three levels, namely pivotal, important and ordinary nodes. Famous scenic spots and traffic hubs are the most important sites that tourists visit. Moreover, the travel route can be divided into four types: synthetic routes, urban-center routes, the Qujiang travel route, and the Lintong travel route. The findings can provide a foundation for tourism cooperation, tourism planning, accurate marketing, travel route design, and other works.