【摘要】 劳动力、资本、信息和知识等生产要素的加速流动，强化了全球城市区域之间的内在联系，不同来源的“流数据”为城市网络研究提供了强大的数据支撑.论文选择反映交通流的铁路客运数据和反映信息流的百度指数数据，运用社会网络分析和流联系强度等方法，对我国城市网络节点和层级结构进行比较研究.结果表明：(1)基于两种数据的中国城市网络节点中心性空间分布差异显著，突出表现在交通枢纽城市对交通流城市网络控制力，东部沿海地区和省会城市对信息流网络的控制力，信息流网络的核心城市对整体网络的整合能力远强于交通流网络，这折射出特大城市对城市空间关联的引导作用.(2)信息流对距离的敏感度较低，在网络层级结构中的复杂程度高于交通流.交通流依托“四横四纵”的铁路干线网络，构成密度较低带状分布网络结构；信息流依据其超空间性，构成密度较高的跨区域复杂网络结构.(3)提升各网络节点综合实力和优化其空间布局是城市网络优化的必由之路.更多还原

【Abstract】 Accelerating flow of labor, capital, information and knowledge strengthens the internal relationship between global urban regions. Stream data from different sources provide powerful data support for the urban network research. Using the methods of social network analysis and flow connection intensity, this paper makes a comparative study on the nodes and hierarchical structure of urban networks in China by selecting the data of railway passenger traffic and the data of Baidu Index, which reflect the information flow. The conclusions are as follows.(1) There is a significant difference in the central spatial distribution of urban network nodes in China between the two flow perspectives, especially in the urban network control of the transportation hub city over the traffic flow, control of information flow networks in eastern coastal areas and provincial capitals. The core city of information flow network integrates the whole network much better than the traffic flow, which reflects the leading role of megacities in urban spatial connection.(2) The information flow is less sensitive to distance and more complex in the network hierarchy than the traffic flow. The traffic flow relies on the "four horizontal and four vertical" railway trunk network to form a low-density zonal distribution network structure, and the information flow is based on its hyperspace to form a high-density complex network structure across regions.(3) Improving the comprehensive strength of network node and optimizing its spatial layout is the only way to optimizing urban network structure.更多还原