中国东部沿海5大城市群旅游流网络结构空间分布特征研究

基于大数据挖掘的旅游流网络结构研究,是旅游流深化研究的主要方向之一。论文基于网络爬虫技术抓取携程旅行网上的中国东部沿海5大城市群旅游线路相关数据,构建城市群旅游流网络,进一步利用社会网络分析法从网络密度、节点结构特征、网络凝聚子群、核心—边缘特征、结构洞等方面揭示旅游流网络结构特征。主要结论有：中国东部沿海5大城市群旅游流网络结构具有层级性和位序—规模特征;各凝聚子群内部联系较为紧密,但各子群之间的互动较少;核心区均位于长江三角洲城市群,核心节点对边缘节点的“涓滴效应”有限;北京、厦门、青岛、广州、中山、杭州等城市在旅游流网络中的结构洞优势较为明显。大数据视角下的旅游流空间网络结构特征的揭示,对于深入认知“流空间”的内涵以及优化城市旅游空间布局具有重要意义。

Spatial distribution characteristics of network structure of tourism flow in five major urban agglomerations of coastal China

The research of tourism flow network structure based on big data mining is one of the main directions of advanced tourism flow research. Using web crawler technology, this study captured the tourism flow data of five major urban agglomerations in coastal China from Ctrip, then examined the spatial structure of tourism flow network, and analyzed the spatial network structure characteristics of tourism flow from the aspects of network density, node structure, network aggregation subgroups, core-periphery characteristics, and structural holes. The results show that: Firstly, the tourism flow network structure of the five major urban agglomerations in coastal China has hierarchical and rank-size characteristics. Secondly, the cohesive subgroups are closely related to each other, but there is little interaction among them. Thirdly, the core areas are all located in the Yangtze River Delta urban agglomeration, and the "trickling down effect" of the core nodes on the peripheral nodes is limited. Lastly, Beijing, Xiamen, Qingdao, Guangzhou, Zhongshan, and Hangzhou have obvious advantages in the tourism flow network. Revealing the characteristics of spatial network structure of tourism flow using big data is of great significance for further understanding the connotation of flow space and optimizing the spatial layout of urban tourism.