文献类型：期刊文献

英文题名：Building a Spatially-Embedded Network of Tourism Hotspots From Geotagged Social Media Data

作者：Wu, Xinyu[1,2,3];Huang, Zhou[1,3];Peng, Xia[4];Chen, Yiran[1,3];Liu, Yu[1,3]

第一作者：Wu, Xinyu

通讯作者：Huang, Z[1];Huang, Z[2]

机构：[1]Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China;[2]Minist Land & Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen 518034, Peoples R China;[3]Peking Univ, Beijing Key Lab Spatial Informat Integrat & Its A, Beijing 100871, Peoples R China;[4]Beijing Union Univ, Tourism Coll, Collaborat Innovat Ctr Tourism, Beijing 100101, Peoples R China

第一机构：Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China

通讯机构：[1]corresponding author), Peking Univ, Inst Remote Sensing & Geog Informat Syst, Beijing 100871, Peoples R China;[2]corresponding author), Peking Univ, Beijing Key Lab Spatial Informat Integrat & Its A, Beijing 100871, Peoples R China.

年份：2018

卷号：6

起止页码：21945-21955

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20181705055144);Scopus(收录号：2-s2.0-85045759376);WOS:【SSCI(收录号:WOS:000431963900001)，SCI-EXPANDED(收录号:WOS:000431963900001)】；

基金：This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFB0503602, in part by the National Natural Science Foundation of China under Grant 41771425, Grant 41625003, and Grant 41501162, in part by the Beijing Philosophy and Social Science Foundation under Grant 17JDGLB002, and in part by the Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, under Grant KF-2016-02-023.

语种：英文

外文关键词：Tourism hotspot network; complex network; geotagged data; social media; big data

摘要：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 spatially-embedded 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 small-world. 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.