Social Network Analysis and Connection Strength Evaluation of Urban Tourist Attractions Using Car-Hailing Data: A Case Study of Beijing

摘要

For large cities with huge tourism market, tourism travels can have significant impact on the urban traffic, which, cannot be ignored in both urban transportation and tourism planning. This paper first proposes a simple and effective spatial matching method to identify tourist travel patterns based on massive online car-hailing data. Then we construct the tourist attractions network based on the tourist movement by car. From the perspective of social network analysis, the development status of the holistic tourist attractions network and the influence of the attractions are evaluated. Finally, connection strength based Jenks natural breaks classification method is employed to divide the attractions into four levels: unconnected, weak, moderate and strong connection. Taking Beijing as case study, the main factors that affect the connection strength among attractions are the popularity of the attraction and the spatial proximity of the attraction. These findings in tourist movement can facilitate authorities and planners to develop tourism destinations and manage tourism traffic better.