城市网络是近年来城市与区域研究的一个新方向.基于2003-2013年间8个横截面的中国铁路客运班列数据,采用加权度中心性和社区结构模型,探讨高速铁路建设对城市等级和集聚性空间格局及演化的影响.研究表明:① 基于铁路客运组织的城市等级结构呈现出位序--规模分布的特征和集聚性,且三大地带和各社区内城市也呈现出明显的位序--规模分布,随着高速铁路网络的扩展,加权度中心性的集聚性更明显,并逐步呈现出较为明显的层级结构和社区结构.② 城市等级结构呈现出明显的东中西地带性,廊道效应和经济,人口的耦合性,即基于铁路客运班列的城市等级结构与基于属性数据(人口/GDP)的结果表现出较大的相似性,但也存在一定的差异.城市社区结构与中国高速铁路网络,城市群的空间分布格局基本一致.随着高速铁路的建设,东中西三大地带间城市等级的差异呈扩大态势,但各社区间城市等级的差异呈缩小态势,部分社区核心城市已形成.

The evolution of inter-city network influenced by globalization and information technology has become a hot topic in city and urban research. This study tries to explore the evolution of nodal hierarchy and communities in inter-city network based on passenger train network during the rapid development period of High-speed Railway (HSR) in China since 2003. Results indicate that: (1) the evolved HSR network in China enlarged the disparities of weighted degree centrality between regions, but decreased the disparities of that between communities, and led to an increasing concentrated city hierarchy with fewer cities having high centrality value, and a growing similarity between the city hierarchies measured by the passenger train network and by city attributes (such as population and GDP); (2) the city hierarchy measured by passenger train network followed a rank-size distribution in the national and regional levels, as well as in some communities. (3) Spatially, cities with higher hierarchy in passenger train network and larger improvement in weighted centrality indicator were mostly located in the eastern region or the areas with the distance to the nearest HSR stations below 50 km, developed economy and high population density; the cities in 2013 could be divided into 14 communities, including the communities with cities mainly located along Beijing-Shanghai, Beijing-Wuhan and Wuhan-Chengdu, Wuhan-Guangzhou, Beijing-Jiujiang, Hangzhou-Xiamen, Lanzhou-Urumqi trunk rail lines, and located in Northeast China, Shanxi Province, Inner Mongolia. (4) The evolution of communities was mostly influenced by the natural environment and administrative areas, especially by the development of HSR network.

交通流是人流、物流等要素流动的主要载体和表现形式,对于认识城市间相互作用等具有重要意义。基于城市间公路、铁路和航空客流数据,对中国城市网络空间关联进行特征提取和规律挖掘。研究表明：① 公路流表现出强烈的空间依赖性和对城市群发育程度的良好识别作用;② 铁路流呈现出“两横三纵”带状分布格局;③ 航空流视角则基本形成了以“菱形结构”为核心的城市网络框架。不同类型交通流刻画出不同层面的城市间关联格局,但却有着其内在联系。航空流是城市关联格局骨架构筑的主要形式,铁路流则为核心骨架的连通提供支撑轴带,而公路流是对整体骨架和支撑轴带的有效填充,从而形成区域间相互依赖、不可或缺的要素关联和空间关系。

Traffic flow acts as a major carrier of other flows (including people, goods, capital, etc.), thus the study on traffic flow is of great significance to understand intercity interaction. Based on the 321 cities at prefecture level or above, this article explores spatial linkage of China's city network using intercity linkage data of road, rail and air transport. The research results show that: (1) The spatial correlation of city network based on road linkage displays strong spatial dependence, which is very useful to identify urban agglomerations and assess developments. Besides the most developed regions including Yangtze River Delta, Pearl River Delta and Beijing-Tianjin-Hebei urban agglomerations, some important urban agglomerations have emerged, such as Zhongyuan, Harbin-Daqing-Qiqihar, Central Jilin, Central-southern Liaoning, Shandong Peninsula, Guanzhong, West coast of Taiwan Straits, Wuhan, Central Yunnan, Changsha-Zhuzhou-Xiangtan. (2) The railway linkage flow reflects intercity external connection pattern, regional element relevancy and regional accessibility along with national railway artery. "Two horizontal and three longitudinal" zonal distribution patterns composed of Beijing-Guangzhou, Beijing-Harbin, Beijing-Shanghai Railway and Longhai-Lanxin, Shanghai-Kunming Railway, constitute the urban network backbone and have become the most important economic axial belts for national territorial development. (3) The "diamond structure" as the core framework basically forms the skeleton of urban network system from the perspective of air passenger flow, whose vertices are Beijing, Shanghai, Guangzhou-Shenzhen and Chengdu-Chongqing. Generally speaking, different types of traffic flows reflect different patterns of intercity linkage, namely, there also exists internal relationship. Air passenger flow constitutes the backbone of intercity linkage pattern, railway linkage flow acts as supporting axis belts for the core framework, and road linkage is a bridge connecting main skeleton and supporting belts. All types of traffic flows collectively form interdependent and indispensable element correlation and spatial relationship among regions.

基于当前城市网络和金融地理研究,以全国336个地级以上行政单元(城市)为研究对象,以33家国内外银行的88022个网点各城市间的级别和数量分布为基础数据,运用链锁模型、Zipf法则、社会网络分析等研究方法,对中国市间联系和城市节点的结构特征进行分析。研究表明：京津冀、长三角、珠三角、成渝和长江中游等五大城镇密集区之间的联系成为这一网络的主干,东西部网络密度以胡焕庸线为界呈现明显差异;城市联通度的规模分布符合Zipf法则,但呈现明显的双分形特征,各城市的节点度同样以胡焕庸线为界在东西部呈现显著差异;此外,国有银行、股份制银行和外资银行所分别对应的城市整体联通度和相对联通度在空间分布上也存在明显差别;上述结构特征同各城市经济规模和人口规模之间存在较强的相关性。从形成机制上看,朝向集中化和均衡化的一般空间政策和行业空间政策对这一网络格局的形成具有深刻影响。

This article analyzes the structural features of China's city network based on bank branches data covering 33 domestic and foreign banks as well as 336 urban administrative regions. The data, which includethe spatial distribution of these branches and their ranks and quantity, are processed using the interlocking world city network (IWCN) model, Zipf law, and social network analysis (SNA). The conclusions are as follows. (1) The connections between five major city agglomerations (Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, Chengdu-Chongqing, and the middle reaches of the Yangtze River) serve as backbones of the network, and a significant difference of network density between eastern and western China as divided by the Hu Line is discovered. (2) The urban size distribution of interlock connectivity conforms to the Zipf law with a double fractal, and the distribution of each city's degree also suggests a significant difference between cities in eastern and western China. (3) The overall and relative interlocking connectivity of the top 50 large cities vary according to the types of banks that include state-owned, joint-stock, and foreign-owned. (4) A relatively strong correlation between connectivity and economic/population size of cities are also found. The structure of this urban network can be interpreted in terms of general spatial policy and industrial spatial policy, in which the interplay between differentiation and equalization shapes the unique and changing pattern of China's interurban bank network.

以高端归国人才为对象,通过构建“归国人才三角”概念框架,设计基于高端移动性人才的城市关系构建方法,对人才迁移驱动的城市网络构建进行了初步探讨。研究认为：① 借助“行动者空间移动带来的空间动力”这一视角,运用高端归国人才在城市间的移动模拟城市间关系,可为构建城市网络提供一条新路径。② 基于人才流动的城市网络构建,有助于破解城市关系矩阵数据挖掘与案例城市选取的难题,是知识经济时代城市网络研究的新方向。③ “归国人才三角”概念框架将人才流动与城市网络两方面研究融为一体,既可以通过人才流动探讨城市创新空间组织特征,也可以通过城市网络方法分析人才流动网络,对城市网络研究和人才战略实施都具有一定参考价值。

As one of the important contents of urban geography, regional urban spatial organization is turning from the traditional city system research to the city networks research. There are two methods to construct city networks. One is using the relational data including the goods flow, capital flow, information flow, population flow among the city to construct city networks; the other one is building models to simulate the relationship between the city, such as interlocking network model and the gravity model. Inspired by the view of the "a spatial dynamic that changes whenever actors move in space" proposed by Menzel, this paper attempts to construct the city networks by using returnees' movement between cities. First, this paper discusses the theoretical relationship between talent mobility and city network. Relational economic geography uses the idea of "based on construction of individual relationship " into network analysis, evolutionary economic geography puts forward the thought of "dynamic proximity", and the research of early uses mobility of talents of high technology to measure the relationship between cities. These had laid a theoretical foundation for the construction of the city network based on the flow of talents movement. Then, we establish the conceptual framework of "triangle model of Chinese returnees". The returnees have the fellow villager's relationship resources in their native places, the classmates' relationship resources in overseas cities and the coworkers' relationship resources in the work city, and these are used in the analysis framework. By integrating the migration data of the returnees, we establish the cities' connections based on the flow of talent, and design a method to calculate the city connectivity. Finally, we select 6 high-end returnees of an innovative team in China to carry out a case analysis. Through the mining of the returnees' city resumes, we successfully construct the city network composed of six talents. As a result, it is suggested that: (1) city innovation network should be examined at national scale under global perspective, and the returnees are good carriers in such researches; (2) the "triangular model" reflects Chinese characteristics, which can explain the formation mechanism of city innovation network better; (3) the returnees team in Beta Pharma Co., Ltd is a typical case that it successfully facilitates inter-city innovation cooperation; and the "triangular model" framework provides a brand-new perspective and analytical method to further research on city innovation network. It should be noted that this paper focuses on theory construction and method exploration, and it needs to use a great quantity returnees' data to carry out systematic research on urban network in the next step, in order to make a greater contribution to urban network theory and the strategy of talents creative practice.

基于春运人口流动大数据,选取对外联系度、优势流、城市位序-规模分析等方法对转型期中国城市网络特征进行分析。结果显示：① 城市网络层级结构中蕴藏着位序-规模规律,但与理想的帕累托分布有所区别,城市规模彼此差异相对较小;② 空间距离与城市等级在城市网络联系中发挥支配性作用,保证了城市网络的层级性与有序性;③ 中国城市网络核心联系呈现“两横三纵”特征,该特征与铁路大动脉的空间分布高度吻合;④ 东部地区城市网络联系更加密切,而西北、西南地区则相对稀疏,基本上以“胡焕庸线”为界,而“兰新线”是突破这一限制的潜在力量;⑤ 中国东北地区未形成明显的区域性中心,城市联系形成带状网络;⑥ 华北与华南地区的“灯下黑”现象值得警惕,缓解这一问题的可行办法是核心城市功能的对外疏散,加强核心城市与周边城市之间的联系;⑦ 带状区域发展或许将成为未来中国区域经济发展的流行模式和中坚力量。总体上看,针对于揭示转型期中国城市网络结构特征,春运人口流动数据具有一定的研究价值,是城市与人口研究领域一个值得深入挖掘的重要数据源。

<p> The space of flows theory proposed by Manuel Castells has given birth to the network perspective of city network. In contrast with the traditional perspective of urban system which is based on the central place theory, city network perspective pays more attention to the interactions and linkages between cities and regions. Thus, the city network is becoming one of the new and hot topics in the field of urban geography. “Chunyun” is a well-known socio-economic phenomenon unique to transitional China, which refers to a blooming of population flows during the Spring Festival, or refers to the period when the blooming happens. Previously, the real population flows data in “Chunyun” were difficult to obtain. The situation had not changed until the “Big data on human migration during the spring festival from Baidu map” (“Baidu migration data” in short) came up. The big data were gathered from the locations provided by hundreds of millions smart phone users through Location Based Service (LBS) Baidu map data source, and was published in the form of interactive heat map that displays people’s travel routes in China during the Chunyun period. Based on Baidu migration data, using degree of external linkages, dominant flows and network-based rank-size analysis, the spatial pattern of city network in transitional China was studied in this article. The study process certificates that Baidu migration data is indeed a high quality data sources for the study of city network, and has turned up some interesting results: 1) The distribution of external linkage degree of cities in China follows Zipf’s law, but differs from the ideal Pareto distribution. 2) The factor of spatial distance and city level play key roles in the formation of urban network of China, and ensure the hierarchy and regularity of the network. 3) The spatial distribution of core linkages in the city network could be summarized as “Three-horizontal & Two-longitudinal”, which almost coincides with the rail arteries in China. The “Three-horizontal & Two-longitudinal” linkages are skeletons of the city network, which matter a great deal in building the interregional contact and coordinating the interregional relationship. 4) In overall, the strength of interactions within the city network differs between East and West China, and Hu's line is apparently the dividing line. As potential powers, the linkages along the Lanzhou-Xinjiang railway line have the opportunity to break the Hu's line. 5) Northeast China lacks regional centers and the linkages between cities forms a bunchy network. 6) There is a phenomenon of “near field deprivation” in North China and South China, that is, the core city have strong interactions with outer regions, but the smaller cities in its near field have poor external linkages with the core city and outer regions. 7) Belt-shaped region may become a popular mode and the future backbone of regional economic development in China.</p>

迁徙流作为互联网时代的新产物,信息流、资本流、交通流等流空间的基本载体,能客观地反映城市间地理行为关系,对于刻画城市网络结构具有重要意义。基于地级以上城市的百度迁徙大数据,本文尝试从全域和净迁徙的视角探索研究中国城市网络结构特征,对其网络的层级、关联关系和影响因素等进行挖掘提取。研究发现：① 全国城市网络呈现出稳定的、层级明确的三棱锥四顶点&#x0201c;钻石型&#x0201d;结构,与主要城市群的经济规模空间分布相吻合;② 区域网络表现出向高级别行政中心集聚的&#x0201c;核心&#x02014;外围&#x0201d;放射状结构;③ 以省会城市为核心的典型小世界特征比较凸出,小世界网络的可达性和连通性较高;周口、阜阳、赣州、上饶、重庆等作为主要劳动力输出型城市,深圳、东莞、广州、北京、上海等城市成为了主要的外来人口聚集地,并形成了对应的人口就近输送网络关系;④ 城市的行政地位、经济规模、交通枢纽建设、劳动力资源等因素都对其网络控制力和影响力起到了决定性作用。最后,研究结合中国城市网络结构特征及其主要影响因素,提出相关政策建议,以期为中国城市网络结构均衡发展与建设提供借鉴依据。

信息技术影响下的城市区域空间结构变化得到了国内外学者的关注。本文以新浪微博为例, 从网络社会空间的角度入手, 对中国城市网络发展特征进行了研究。研究表明:微博社会空间视角下的中国城市网络存在着明显的等级关系与层级区分, 城市的网络连接度与城市等级表现出了相对一致性。根据城市网络层级与网络联系强度, 东部、中部、西部3 大区域板块的网络联系差异明显, 东部地区内部的联系, 以及东部与中部地区和西部地区的联系几乎构成当前网络体系中的全部。城市网络呈现出分层集聚现象, 具体表现为“三大四小”发展格局, 即京津冀区域、珠三角区域、长三角区域、成渝地区、海西地区、武汉地区、东北地区。高等级城市在整个城市网络中处于绝对支配地位, 北京以突出的优势成为全国性的网络联系中心, 而上海、广州、深圳则成为全国性的网络联系副中心。

The change of urban regional spatial structure influenced by information technology has become a hotspot of research at home and abroad. This study tries to analyze China's city network characteristics from the social network space perspective by using Sina microblog as an example. The result shows that China's city network based on the micro-blog social space has a clear hierarchical structure and level distinction. Firstly, the result shows the existence of regional characteristics, performance as a visible regional development pattern which contains "Three Main-regions and Four Sub-regions" according to the analysis of the level distinction in the city network and the connection rate between cities. Specifically speaking, the three main regions contain the Beijing-Tianjin-Hebei region represented by Beijing, Pearl River Delta region represented by Guangzhou and Shenzhen, and the Yangtze River Delta region represented by Shanghai, Hangzhou and Nanjing. The four sub-regions contain Chengdu-Chongqing region, west coast of the Taiwan Straits region represented by Fuzhou and Xiamen, Wuhan region represented by Wuhan and Changsha, Northeast China represented by Shenyang, Harbin and Changchun. Secondly, the result shows there is a significant difference of the network links among Eastern, Central and Western China. Links within Eastern China and the links between Eastern, Central and Western China constitute almost all of the current network systems. It is also found that the high-level cities have an absolute dominance in the city network pattern, and that Beijing is the contact center in China's city network, with an overwhelming advantage. Shanghai, Guangzhou and Shenzhen are the sub-contact centers in the China's city nework.

空间联系强度是城市群发展阶段、态势、功能定位的重要表征.在大数据背景下，随着移动终端的普及和网络联系平台的广泛使用，人流在不同地区的空间移动能够得到较准确的统计和表达.在总结以往城市群空间联系研究方法的基础上，提出一种新的基于微博数据判别城市之间空间联系强度的方法，弥补了由于缺乏城际通勤数据而导致的传统空间联系强度判别方法的不足.新方法可以较准确地判别城市群地区各个城市的空间联系强度与组织类型.

Spatial connection intensity is an important indicator for the development stage, situation, and function position of urban agglomeration. With the wide use of mobile terminals and networking platform, population mobility among different regions can be traced and expressed more accurately by using big data analysis technique. Based on the database of microblog, a new measurement method for spatial connection intensity is proposed in this study. The new method makes up for the traditional disadvantages resulting from the lack of commuting data. Therefore, it provides guidance for accurate identification of urban agglomeration.

人居活动是城市网络的根本,探究城市人居活动网络结构对促进区域协调发展具有重要的实践意义。论文利用百度贴吧数据分析城市人居活动,运用社会网络分析法等研究方法探究城市人居活动网络体系,并通过QAP论文相关及回归分析对城市人居活动网络结构影响因素进行初步分析。结果表明：① 整体网络方面,人居活动区域联系密度为95.99%,东北三省城市之间普遍存在联系;城市联系类型可划分为全域型、普遍型、较多型、一般型以及较少型五种类型;② 层级结构方面,东北三省省内人居活动网络层级较为明显,区域范围内尚未形成主导型城市及次级主导型城市;③ 城市体系方面,省内人居活动网络体系较为完备,形成了较为明显的城市网络体系;④ 影响因素方面,旅游资源、行政关系、空间邻近及收入水平对城市人居活动网络结构产生显著影响。

Human habitat activity is the foundation of urban network. Examining the network structure of human habitat activities has important practical significance for promoting regional coordinated development. This study used Baidu Post Bar data to characterize urban human habitat activities, employed a social network analysis method to study the urban human habitat activity network system, and used quadratic assignment procedure (QAP) correlation and regression analysis to analyze the influencing factors of urban human habitat activity network structure. The results show that: 1) In terms of the overall network, the density of contact in the habitat activity area is 95.99%, and there are widespread connections among the cities in the three northeastern provinces. Urban connections can be divided into five types: global, common, relatively high, medium, and relatively low. 2) Urban human habitat activity network hierarchy at intraprovincial level is more obvious, and dominant cities and sub-dominant cities have not yet formed within the regional scope. 3) The network system of human habitat activities within the provinces is relatively complete, forming a relatively obvious urban network system. 4) In terms of influencing factors, tourism resources, administrative relations, spatial proximity, and income levels have significant impacts on the formation of urban human habitat activity networks.

基于实际发生的信息流研究流空间网络格局是一种新的尝试。以吉林省县级以上地方为研究单元，以各地间固定电话通话时长为原始数据，采用主成分分析法、C-Value 和D-Value层级分析法、优势流分析法、最小生成树法对吉林省流空间格局进行了分析。研究表明：吉林省流空间是以长春市为中心，长春市、延吉市、通化市、公主岭市为主导型城市，吉林市、白城市、白山市、辽源市、松原市、四平市为次级主导型城市，其他城市为从属型城市的层级化网络结构；行政区划在流空间格局中发挥基本的影响作用；以长春市为&ldquo;单中心&rdquo;的流空间特征明显，吉林省并无明显的次中心作用，长春市与吉林市流空间联系并不紧密，与传统认识和意愿有所不同；公主岭市和敦化市在吉林省流空间格局中占有重要地位，公主岭市倾向于融入长春城市圈，敦化市在吉林省东部空间网络格局中发挥了重要作用，两市的区域联通功能亟待挖掘；四平市和梨树县流空间联系紧密，适宜同城化发展。

随着现代交通、通信以及信息技术的发展,基于网络社会的“流空间”成为研究城市群空间结构的重要理论前沿。借助珠三角城市群9个城市的人流、物流、资金流和信息流数据,对珠三角城市群空间结构的现状和发展趋势进行综合性判断。研究发现：① 珠三角城市群的空间结构现状在“点-线-网-面域”4个层面均呈现出明显单极化态势,广州市是“流空间”视角下珠三角城市群的核心,区域网络结构呈现出“缺位型金字塔形结构”;② 珠三角城市群网络的未来发展中位于不同层级的城市将起着不同的作用,其中广州、深圳、东莞等城市对空间结构发展起着导向性作用,而佛山、中山等城市将承担着联系中转站功能;③ 珠三角各城市的流度辐射区一体化明显,各城市辐射影响区的空间形态也表明了各城市的功能圈和势力范围。未来随着全球化趋势和区域一体化政策的加强,珠三角城市群的集聚效应将不断转化为扩散效应,将极大提升珠三角城市群对全球范围内资源的吸聚和配置能力,助力珠三角城市群走向网络化的发展时代。

With the development of modern transportation, communication and information technology, the "space of flow" based on network society has become an important theoretical frontier for studying urban spatial structure. Based on the passenger flow, material flow, fund flow and internet information flow in nine cities of the Pearl River Delta, this paper makes a comprehensive judgment on the present situation and development trend of spatial structure of urban agglomeration in this region. Research findings are as follows: (1) The present situation of urban spatial structure in the Pearl River Delta presents obvious unipolarization, and Guangzhou is the core of the delta based on the "space of flow". (2) Cities at different levels will play different roles in the future development of the urban agglomeration network. Guangzhou, Shenzhen and Dongguan play a leading role in the development of spatial structure, while Foshan, Zhongshan and other cities will assume the function of connecting transit stations. (3) The urban areas of the Pearl River Delta are well integrated. The spatial form of the radiated area of each city also indicates the functional circle and sphere of influence of each city. In the future, with the strengthening of globalization and regional integration policies, the agglomeration effect of the Pearl River Delta region will be transformed into diffusion effect, which will greatly improve the ability of the delta to absorb and allocate resources on a global scale.

区域一体化下的跨界合作与产业协同有利于推动区域高质量发展与实现共同富裕。论文借助流空间网络、耦合分析、探索性空间分析等方法系统分析2010&#x02014;2019年粤港澳大湾区区域合作与产业一体化的演化特征及耦合关系,得到的主要结论有：① 大湾区区域合作突破地理邻近性,网络化趋势明显加强,城市网络联系指数整体上升;② 大湾区城市产业布局、要素一体化过程中极化效应显著,产业发展内部差异悬殊;③ 大湾区区域合作与产业一体化的耦合协调度整体上升,其空间演化呈集聚趋向,空间布局结构具有局部稳定性,整体分布格局呈&#x0201c;东南独高、中北趋凸、周边低凹&#x0201d;的特征;④ 大湾区西部及东南沿海城市耦合协调度空间增长过程具有显著的负向整合性,大湾区耦合协调度空间演化具有空间依赖性。研究表明大湾区区域合作与产业一体化具有显著的时空关联性,大湾区应持续推进多层次、全方位的区域合作,促进产业一体化与区域合作的高度耦合。

Under the background of regional integration, cross-boundary cooperation and industrial development are conducive to promoting regional high-quality development and common prosperity. By means of space of flows network, coupling analysis, and exploratory spatial analysis, the evolution and coupling relationship between regional cooperation and industrial integration in the Guangdong-Hong Kong-Macao Greater Bay Area are quantified from 2010 to 2019. The main conclusions are as follows: 1) Regional cooperation has transcended geographical proximity, the networking trend has been significantly strengthened, and the network connectivity index of cities generally has increased in the study area. 2) The study area shows significant polarization effect of urban industrial layout and factor integration, and there are great differences in industrial development. 3) The coupling coordination degree between regional cooperation and industrial integration has increased as a whole. The spatial evolution of coupling coordination degree between regional cooperation and industrial integration showed an agglomeration trend, its spatial layout structure shows local stability, and the overall distribution pattern shows the characteristics of "a unique height in the southeast, convex in the middle and north, and low and concave in the surrounding areas". The spatial growth process of coupling coordination degree of western and southeastern coastal cities shows significant negative integration in the study area. However, the spatial evolution of coupling coordination degree shows spatial dependency. The research indicates that there is a significant temporal and spatial correlation between regional cooperation and industrial integration in the study area, and the area should continue to carry out multi-level and all-round regional cooperation to promote the high degree coupling of industrial integration and regional cooperation.

基于抖音粉丝量数据,运用位序-规模法则、核密度估计、领域划分与模式组合等方法,对中国城市网络关注的空间差异进行分析,并对比了其与传统百度指数的差异。研究发现：① 关注度排名靠前的城市分别是北京、上海、广州、深圳、成都、杭州、重庆、西安、天津、南京等,并形成了长三角、珠三角、京津三大核心集聚区,反映出核心经济发展区的网络优势度。而中西部地区城市的关注度普遍不高,仅在成渝、中原、长江中游等地区形成微弱的集聚中心。② 从位序-规模法则看,拟合曲线偏离理想状态且q值大于1.3,反映出高关注城市在空间上的强影响作用并表现出一定的网络空间集聚效应。从四大分区看,东北和西部地区与整体类似,东部地区的高等级集聚效应进一步强化,而中部则较符合理想形态。③ 从领域划分与地域模式看,北京、上海、广州等高关注城市的核心领域是探店、旅游、美食、街拍、同城,方言、旅游类话题亦有较大的关注。中西部地区核心城市除了在特色美食、探店、街拍与东部地区有些类似外,还表现出房产、地铁等方面的特色,从侧面反映出该区域在城镇化建设、产业转型等方面面临的一些现实问题。从地域模式看,长三角属于多中心网络化,京津冀、珠三角、成渝、长江中游属于双中心点轴状,关中、中原属于单中心放射状,其余城市群则属于单中心或无中心离散状。④ 与百度指数对比看,抖音粉丝量在高水平区的集聚程度高,而在中西部城市群地区的集聚效应不明显。⑤ 从影响因素看,除了与经济发展水平尤其是现代服务业水平、信息化水平、交通物流保障相关外,与城市的创新性、高素质人才或高学历网民的活跃性参与、数字化推广、专业化运营相关性较大。

Based on the data of Douyin fans and Baidu index, we adopted the rank-size model, kernel density estimation, field division, and regional combination to examine the spatial differences of urban network attention, and carried out a comparative analysis. Some conclusions can be drawn as follows. (1) Municipalities and provincial capitals, such as Beijing, Shanghai, Guangzhou, Shenzhen, Chengdu, Hangzhou, Chongqing, Xi'an, Tianjin, and Nanjing, are cities that draw high attention, which are in accordance with some agglomeration regions such as the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin region. However, cities with low attention are concentrated in agglomeration regions with small and low-density population, such as Chengdu-Chongqing, Central China Plains, and middle and lower reaches of the Yangtze River. (2) From the perspective of the rank-size model, the fitting curve deviates from the ideal state and the q-value is greater than 1.3, reflecting the strong spatial agglomeration effect of high-grade cities in network space. Specifically, the curves of northeastern and western China are similar; that of central China is close to the ideal form; and the high-level agglomeration effect in eastern China is further strengthened according to the data. (3) From the perspective of field division and regional model, the core fields of high attention cities such as Beijing, Shanghai, and Guangzhou are shop exploration, tourism, food, street photography, and entertainment. As for central and western China, the main attractions are real estate, and subways, as well as special food, shop exploration, and street photography. (4) From the perspective of spatial combination, the Yangtze River Delta belongs to multi-center network type, Beijing-Tianjin-Hebei region, Pearl River Delta, Chengdu-Chongqing region, and the middle reaches of the Yangtze River belong to double-center point-axis type, Guanzhong and Zhongyuan urban agglomerations belong to single-center radiation type, and other urban agglomerations belong to single-center or has no-center type. (5) Based on the comparison of Baidu index, cities with high-level network attention are concentrated in eastern China, while the network effect in central and western China is not obvious. (6) In terms of influencing factors, the formation of all these patterns is closely related with the innovation level, digital promotion, and specialization operation of high-quality talents or highly-educated netizens, in addition to economic level with regards to the levels of the modern service industry, informatization process, and transportation.

直播带货是在互联网时代快速崛起的新兴电子商务业态,同时也是粉丝经济的表现形式之一,已有文献缺乏从地理学视角对粉丝经济开展研究。论文基于网络空间理论,以抖音带货主播为例,结合电子商务的影响因素及城市舒适性理论构建了影响中国带货主播空间分布的指标体系,运用区位熵、莫兰指数、冷热点分析方法,对中国带货主播的空间集聚特征进行了可视化分析,通过空间回归模型探析了影响带货主播的地理因子。研究表明： ① 带货主播在空间上呈现显著的集聚现象,且高度集中在东部沿海地区,以广州、杭州最为突出;② 以直播带货为例的粉丝经济正在重塑中国原有的城市等级体系,具有娱乐传媒、电商、旅游特色的城市(如长沙、金华、丽江),对带货主播有很强的吸引力,甚至超过部分一线城市;③ 通过空间回归分析发现,电商创业环境、文化旅游对粉丝经济生产者的空间分布具有很强的解释力,生活便利性与自然环境也具有重要影响;相比而言,人力资本影响较小,专利数量甚至对带货主播具有较明显的挤出效应,说明直播带货具有很强的草根性。研究为揭示粉丝经济的空间过程及其影响因素提供了详实的实证案例,为地方政府推进数字经济发展和制定人才引进政策提供了参考依据。

Fan economy is a rapidly emerging business in the Internet era. However, the existing literature lacks research on fan economy from a geographical perspective. Based on the theory of network space, and taking TikTok livestreaming commerce host as an example, combined with the influencing factors of e-commerce and urban amenity theory, this study constructed an index system of influencing factors affecting the spatial distribution of Chinese livestreaming commerce host. Using location quotient, global Moran's I, and cold-hot spot spatial analysis methods, we analyzed the spatial agglomeration characteristics of Chinese livestreaming commerce host, and the geographic factors that affect livestreaming commerce host distribution through spatial regression. The results indicate that: 1) China's fan economy shows a significant spatial agglomeration, and it is highly concentrated in the eastern coastal areas, with Guangzhou and Hangzhou as the most prominent. 2) The digital economy represented by livestreaming is reshaping China's original city tier systems. Cities with entertainment media, e-commerce, and characteristic tourism (such as Changsha, Jinhua, and Lijiang), are very attractive to livestreaming commerce hosts, even more than some first-tier cities (such as Beijing and Shanghai). 3) Through spatial regression analysis, it is found that the environment for e-commerce startups and cultural tourism have a strong explanatory power for the spatial distribution of livestreaming commerce hosts. The convenience of living and the natural environment also have an important impact, and the impact of human capital is small. At the same time, the number of patents has a significant crowding out effect on livestreaming commerce hosts, and livestreaming commerce has a strong grassroots nature. This research provides detailed empirical cases for in-depth understanding of the spatial process of fan economy and its influence mechanism and provides a reference for local governments to promote the development of digital economy and formulate talent introduction policies.

基于阿里巴巴县域网络购物数据,分析中国1915个县域的网购格局,并利用地理探测器探讨其影响因素。结果表明：① 县域网购格局整体上以江浙为核心、从东部沿海向内陆扩散,但存在由东部沿海向华北地区延伸的高值条带及内陆散落状的高值区,低值集聚区主要在西南、东北地区。② 县域网购水平的核心影响因素是网商水平、城镇化水平、居民收入,二级影响因素是教育水平、信息化水平、物流发达程度,其他因素的影响较小。③ 不同地区县域网购水平的主要影响因素存在较大差异。除城镇化和受教育水平是所有县域的主要影响因素外,中部地区县域还受收入水平、信息化的影响,西部地区县域还受物流发达程度、经济水平、零售水平的影响,东部地区县域还受网商水平的影响。

It is now widely accepted that the world is moving rapidly into the information age and electronic commerce is a major component of this historic transformation. As the most important part of the electronic commerce, E-shopping has been expanding in the last decade, which has pushed forward China into the stage of nationwide online shopping. In recent years, the development of E-shopping is in its heyday, and the research of online shopping and online consumption became more and more popular. County is the new growth point of China's E-shopping and online consumption, but the relevant research is still very deficient. Under this background, based on data from Alibaba Group, this paper tries to analyze the spatial pattern of E-shopping development in China's county applying spatial autocorrelation method, and then discusses its impact factors using Geodetector method. The results show that: (1) The development of E-shopping declined from southeastern coastal counties to the inland counties. On one hand, the counties with high SI concentrated in coastal China, especially in Jiangsu and Zhejiang provinces. There are some high SI counties located along the strips extending from eastern coastal region to north China, and few high SI counties are scattered in inland China. On the other hand, the counties with low SI are concentrated in southwestern and northeastern China. (2) Geodetector results show that, the first-level significant influencing factors of counties' E-shopping pattern are the development of E-business (bi), regional urbanization (urb) and resident income (inc); the second-level factors are population education level (edu), regional information development level (ict) and local logistic system (lgt); while other factors have negligible impacts. (3) There are notable differences in the main influencing factors of county's E-shopping level in different regions. Except that regional urbanization (urb) and population education level (edu) are the main influencing factors of all counties in China, counties in Central China are also impacted by resident income (inc) and regional information development level (ict); counties in Western China are also impacted by local logistic system (lgt), economic development (eco) and local retail industry (ret); counties in Eastern China are also impacted by local E-business (bi). Overall, with the decline of county's SI value from Eastern to Western China, the impact of regional urbanization (urb) and population education level (edu) has increased, while the impact of resident income (inc), local logistic system (lgt), information development level (ict) and local E-business (bi) has decreased.

空间分异是自然和社会经济过程的空间表现,也是自亚里士多德以来人类认识自然的重要途径。地理探测器是探测空间分异性,以及揭示其背后驱动因子的一种新的统计学方法,此方法无线性假设,具有优雅的形式和明确的物理含义。基本思想是：假设研究区分为若干子区域,如果子区域的方差之和小于区域总方差,则存在空间分异性;如果两变量的空间分布趋于一致,则两者存在统计关联性。地理探测器q统计量,可用以度量空间分异性、探测解释因子、分析变量之间交互关系,已经在自然和社会科学多领域应用。本文阐述地理探测器的原理,并对其特点及应用进行了归纳总结,以利于读者方便灵活地使用地理探测器来认识、挖掘和利用空间分异性。

Spatial stratified heterogeneity is the spatial expression of natural and socio-economic process, which is an important approach for human to recognize nature since Aristotle. Geodetector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. This method with no linear hypothesis has elegant form and definite physical meaning. Here is the basic idea behind Geodetector: assuming that the study area is divided into several subareas. The study area is characterized by spatial stratified heterogeneity if the sum of the variance of subareas is less than the regional total variance; and if the spatial distribution of the two variables tends to be consistent, there is statistical correlation between them. Q-statistic in Geodetector has already been applied in many fields of natural and social sciences which can be used to measure spatial stratified heterogeneity, detect explanatory factors and analyze the interactive relationship between variables. In this paper, the authors will illustrate the principle of Geodetector and summarize the characteristics and applications in order to facilitate the using of Geodetector and help readers to recognize, mine and utilize spatial stratified heterogeneity.

知识生产与创新被认为是推动经济增长的关键因素。随着技术变得越来越复杂，复杂知识生产所产生的“知识负担”逐渐超过了独立个人的创新能力，这种情况下，在专业化知识领域与他人的合作被认为是可以减缓这类“知识负担”困境的一种途径。因此，论文根据中国知识产权局1985—2019年间的3012565条专利记录，以中国297个地级及以上城市为例，刻画中国城市专利复杂度的时空演变，并运用Logistic回归模型探究知识复杂度对创新合作的影响。研究发现：① 1985—2019年，中国城市知识复杂度逐年增加，且空间分布不均衡，总体呈现“东高西低、南高北低”的态势；② 专利知识复杂度与合作之间存在着显著正相关的关系，这表明专利复杂度的增加促进了创新合作；③ 复杂性和城市间合作之间存在显著的负相关关系，这说明复杂知识具有一定的空间粘性，相较于复杂度较低的知识，复杂度较高知识的合作更倾向于“本地合作”而非“城际合作”。论文从复杂知识发明的角度为中国区域创新发展的不平衡提供了进一步的解释。

Knowledge production is widely recognized as a critical source of long-term economic growth. However, the increasing complexity of contemporary knowledge production requires inputs exceeding that of the individual. This knowledge burden is dampened to some degree by collaboration. Yet, there is little empirical evidence on the relationship between complexity and collaboration, especially in China. By using the data of more than 3.0 million Chinese patents from the China National Intellectual Property Administration on 297 prefecture-level cities and above in China during the period from 1985 to 2019, this study explored the spatial and temporal evolution of patent complexity and examined the relationship between knowledge complexity and innovation collaboration in Chinese cities. The empirical analysis revealed that: 1) complexity was increasing and was spatially unevenly distributed during this period with an overall trend of high in the east and low in the west, and high in the south and low in the north; 2) there was a robust positive relationship between complexity and collaboration, suggesting that the increase of complexity can contribute to innovation collaboration; and 3) there was a negative and significant relationship between complexity and inter-city collaboration, indicating that complex knowledge is "stickier" than less complex knowledge, and increasing complexity is associated with local rather than nonlocal collaboration.

航空运输是现代交通运输的重要组成部分,以机场和航线构建的网络是其提供运输服务的空间载体。基于复杂网络理论,借助度分布、平均路径长度、簇系数、度度相关性、簇度相关性等指标对以城市为节点的中国航空网络空间结构进行分析,发现其度累计概率分布表现为具有置信度较高的指数分布,且具有较小的平均路径长度(2.23)和较大的簇系数(0.69),整体结构呈现"小世界网络"的特点。由于中国航空网络规模较小,且新建机场倾向于直接与最高级枢纽机场建立航线联系,不利于区域枢纽机场的形成。因而除顶层结构(北京&mdash;上海&mdash;广州)外,中国航空网络的其它层级结构并不十分明显。从节点的度、簇系数、可达性等指标及其相关性分析,中国航空网络空间结构特征差异明显,表现出较强的集聚性,且可达性与城市体系上层结构在空间分布上较为吻合。随着中国航空运输需求的快速增加,未来航空网络在市场经济的推动下,将进一步表现出向具有"无标度"特征的"小世界网络"演变的趋势,航空网络的空间结构将日趋复杂化。

Today, air transport plays an important role in transportation systems, especially for medium and long distance. Based on complex network theory, Chinese aviation network is abstracted as a set of edges (linkages) connecting a set of nodes (cities), and 144 cities and 1018 air routes were chosen for this research operated from winter 2007 to spring 2008. Then, this paper analyzes the spatial structure of Chinese aviation network using indices of degree distribution, the average path length, the clustering coefficient, degree-degree correlation, and clustering-degree correlation. Degree is the number of edges that a node shares with others, and thus symbolizes the importance of the node in the network. Degree distribution is used to reflect the distribution function of degree and donates the statistical characteristics of a network. Average path length is defined as the average number of edges along the shortest paths for all possible node-pairs in the network and it is a measurememt of the efficiency of transportation network. The clustering coefficient of a node is the ratio of actual edges to maximal edges between nodes which are directly connected with the node. The clustering coefficient of the whole network is the average of all individuals. As for an airport network, the average path length and the clustering coefficient are the two most important parameters reflecting network properties and configurations. The results show that Chinese aviation network has a relatively small average path length of 2.23 and a relatively large cluster coefficient of 0.69. More importantly, the accumulative degree distribution follows an exponential expression, with significance of 0.977. Therefore, Chinese aviation network shows the characteristic of a "Small World" network. Due to most new airports' preferences for direct connections with the three top-level national hubs: Beijing, Shanghai, and Guangzhou, the network hierarchy has no distinct difference with the exception of the top one. Also, the spatial distribution of Chinese aviation network is imbalanced according to the indices of degree, clustering coefficient and accessibility index. Besides, the correlation coefficients of these indices mentioned above are analyzed. The results show that there are negative degree correlation, nonlinear clustering-degree correlation, positive accessibility-degree correlation, and slightly positive clustering-accessibility correlation. In conclusion, with the rapid development of air transport demand driven by the market economy, Chinese aviation network will further evolve to a combined model of "Scale Free" and "Small World" networks, and its spatial structure will be more complex.