Mining travel behaviors of tourists with mobile phone data: A case study in Hainan

As the mobile devices are used widely, it is possible to research human mobility and behaviors by using the increasing mobile phone data. This paper aims to mine travel behaviors of users in Hainan, a popular tourist destination in China. The data is Call Detail Records (CDR) and Point of Interest (POI) information. Specifically, a data processing platform is developed. It can convert the large scale of CDR and location-based data to trajectories by utilizing the cross-domain data. Furthermore, a hierarchical analytical method is built on our platform to identify the difference of tourists respectively in temporal and spatial dimensions. Finally, the most popular travel patterns and top 3 travel routes for short-term tourists in Sanya are discovered from the trajectories of tourists according to the platform.