Building a Spatially-Embedded Network of Tourism Hotspots From Geotagged Social Media Data

The rapid development of social media and location-based service has generated a myriad of spatial data tagged with geo-information. Constructing a network of tourism hotspots using these geotagged data would improve our understanding of tourism activities. Thus, using Flickr data, we built a spatiallyembedded tourism hotspot network for Beijing and applied complex network analysis to study the network characteristics. The results indicate that the tourism hotspot network in Beijing is scale-free and smallworld. In the hotspot network, the interconnected triplets have a tendency to be formed by the edges with greater weight values, and a high-weighted edge is often connected by two high-degree vertices. Moreover, the statistics of the network provides insights for additional travel bus routes in Beijing. Finally, this paper provides a guide for building spatially-embedded hotspot networks based on geotagged social media data, which helps to understand the laws of travel and provides decision support for the development of tourism resources.