中国城市信息网络的主干结构与影响机制

戴靓; 王瑞霖; 曹湛; 丁子军; 郑慧彬

doi:10.13959/j.issn.1003-2398.2024.03.012

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人文地理 ›› 2024, Vol. 39 ›› Issue (3) : 113-122. DOI: 10.13959/j.issn.1003-2398.2024.03.012

城市

中国城市信息网络的主干结构与影响机制

戴靓^1,2,3, 王瑞霖¹, 曹湛^4,5, 丁子军¹, 郑慧彬¹

作者信息 +

THE INFLUENCING MECHANISM AND BACKBONE STRUCTURE OF CHINA'S INTERCITY INFORMATION NETWORK

DAI Liang^1,2,3, WANG Rui-lin¹, CAO Zhan^4,5, DING Zi-jun¹, ZHENG Hui-bin¹

Author information +

文章历史 +

摘要

本文通过2019年336个城市间的百度搜索指数构建中国城市信息网络，采用差别化过滤法和指数随机图模型，探讨其主干结构特征与内外生影响机制。研究发现：中国城市信息网络具有高密度、多尺度和异构性，基于差别化过滤法提取的主干网络清晰展现了信息流的地域差异和全局特征。国家级城市群之间形成距离衰减弱、空间跨度大、多元扁平化的信息流通道，并对东北和西南城市形成一定的邻近辐射；成都、重庆、西安形成三角聚合效应；新疆、西藏的信息流较为地域化和边缘化。行政等级、信息化水平、旅游热度能促进城际信息流动，省界效应突出。网络内生的择优连接和关系闭合机制也至关重要，但择优连接强于关系闭合，促使网络向层级性的组团化发展。

Abstract

In the era of Internet, the high-speed flows of information contribute to the dynamic reconstruction of urban space. Against this backdrop, this paper constructed China's intercity information network based on the Baidu searching index of 336 cities at the prefecture level and above in 2019, and then applied disparity filter algorithm to extract the backbone of the complex information network and analyzed its structural characteristics. After that, exponential random graph models were used to further explore the underlying endogenous and exogenous influencing mechanisms. The results show that: 1) China's intercity information network is highly dense with full coverage, multiple scales, and obvious heterogeneity. The network backbone extracted by the disparity filter algorithm at the significance level of 0.1 clearly shows the regional disparity and global features of the intercity information flows. 2) The virtual intercity information flows still suggest an apparent gradient difference of regional development. 3) The city's administrative level, informatization level, and tourism popularity can enhance intercity information flows and the provincial boundary effect is prominent in China.

导出引用

戴靓, 王瑞霖, 曹湛, 丁子军, 郑慧彬. 中国城市信息网络的主干结构与影响机制[J]. 人文地理. 2024, 39(3): 113-122 https://doi.org/10.13959/j.issn.1003-2398.2024.03.012

DAI Liang, WANG Rui-lin, CAO Zhan, DING Zi-jun, ZHENG Hui-bin. THE INFLUENCING MECHANISM AND BACKBONE STRUCTURE OF CHINA'S INTERCITY INFORMATION NETWORK[J]. HUMAN GEOGRAPHY. 2024, 39(3): 113-122 https://doi.org/10.13959/j.issn.1003-2398.2024.03.012

中图分类号： F129.9

参考文献

[1] Castells M. The Rise of the Network Society[M]. Oxford:Blackwell, 1996:453-459.
[2] Capello R. The city network paradigm:Measuring urban network externalities[J]. Urban Studies, 2000,37(11):1925-1945.
[3] 杨亮洁,杨晓蓉,杨永春.城市内生竞争力与外生竞争力耦合协调研究:以成渝城市群为例[J].人文地理,2021,36(6):76-86.[Yang Liangjie, Yang Xiaorong, Yang Yongchun. Coupling coordination study between endogenous and exogenous competitiveness of Chengdu-Chongqing urban agglomeration[J]. Human Geography, 2021,36(6):76-86.]
[4] 潘峰华,方成,李仙德.中国城市网络研究评述与展望[J].地理科学, 2019,39(7):1093-1101.[Pan Fenghua, Fang Cheng, Li Xiande. The progress and prospect of research on Chinese city network[J]. Scientia Geographica Sinica, 2019,39(7):1093-1101.]
[5] 赵金丽,张学波,任嘉敏,等.多元流视角下黄河流域城市网络空间结构及其影响因素[J].地理科学,2022,42(10):1778-1787.[Zhao Jinli, Zhang Xuebo, Ren Jiamin, et al. Spatial structure and influencing factors of urban network in the Yellow River basin based on multiple flows[J]. Scientia Geographica Sinica, 2022,42(10):1778-1787.]
[6] 王波,甄峰,席广亮,等.基于微博用户关系的网络信息地理研究:以新浪微博为例[J].地理研究,2013,32(2):380-391.[Wang Bo, Zhen Feng, Xi Guangliang, et al. A study of cybergeography based on micro-blog users' relationship:With a case of Sina micro-blog[J]. Geographical Research, 2013,32(2):380-391.]
[7] Vinciguerra S, Frenken K, Valente M. The geography of Internet infrastructure:An evolutionary simulation approach based on preferential attachment[J]. Urban Studies, 2010,47(9):1969-1984.
[8] Devriendt L, Derudder B, Witlox F. Cyberplace and cyberspace:Two approaches to analyzing digital intercity linkages[J]. Journal of Urban Technology, 2008,15(2):5-32.
[9] Trasarti R, Olteanu-Raimond A M, Nanni M, et al. Discovering urban and country dynamics from mobile phone data with spatial correlation patterns[J]. Telecommunications Policy, 2015,39(3/4):347-362.
[10] 龚言浩,甄峰,席广亮,等.基于微信公众号文章的城市关注度等级与联系网络研究[J].现代城市研究,2019(4):69-75,131.[Gong Yanhao, Zhen Feng, Xi Guangliang, et al. Research on spatial pattern of city's attention degree and relationship network in China based on WeChat articles[J]. Modern Urban Research, 2019(4):69-75,131.]
[11] Zhang Z, Wang Z. Cyberspace-based urban networks:Visualising and exploring China's intercity interaction from a new perspective[J]. Environment and Planning A:Economy and Space, 2022,54(3):454-460.
[12] Segev E. Googling the world:Global and regional information flows in Google Trends[J]. International Journal of Communication, 2018,12:2232-2250.
[13] Yin J, Soliman A, Yin D, et al. Depicting urban boundaries from a mobility network of spatial interactions:A case study of Great Britain with geo-located Twitter data[J]. International Journal of Geographical Information Science, 2017,31(7):1293-1313.
[14] 丁志伟,马芳芳,张改素.基于抖音粉丝量的中国城市网络关注度空间差异及其影响因素[J].地理研究,2022,41(9):2548-2567.[Ding Zhiwei, Ma Fangfang, Zhang Gaisu. Spatial differences and influencing factors of urban network attention by Douyin fans in China[J]. Geographical Research, 2022,41(9):2548-2567.]
[15] 安頔,胡映洁,万勇.中国城市信息流网络空间结构特征研究:基于降噪处理与有向网络分析方法[J].世界地理研究,2024,33(1):134-148.[An Di, Hu Yingjie, Wan Yong. Analysis on characteristics of urban information network structure in China:A method based on denoising and directed network[J]. World Regional Studies, 2024,33(1):134-148.
[16] 常晓猛,乐阳,李清泉,等.利用位置的虚拟社交网络地理骨干网提取[J].武汉大学学报·信息科学版,2014,39(6):706-710,718.[Chang Xiaomeng, Yue Yang, Li Qingquan, et al. Extracting the geographic backbone of location-based social network[J]. Geomatics and Information Science of Wuhan University, 2014,39(6):706-710, 718.]
[17] Dai L, Derudder B, Liu X. Transport network backbone extraction:A comparison of techniques[J]. Journal of Transport Geography, 2018,69:271-281.
[18] 梅大伟,修春亮,冯兴华.中国城市信息网络结构演变特征及驱动因素分析[J].世界地理研究,2020,29(4):717-727.[Mei Dawei, Xiu Chunliang, Feng Xinghua. Analysis on the evolution characteristics and driving factors of urban information network structure in China[J]. World Regional Studies, 2020,29(4):717-727.]
[19] 刘程军,陈亦婷,陈秋驹,等.企业投资视角下金融科技的空间联系网络演化与影响因素[J].经济地理,2023,43(2):136-146.[Liu Chengjun, Chen Yiting, Chen Qiuju, et al. Evolution and influencing factors of the spatial connection network of financial technology from the perspective of enterprise investment[J]. Economic Geography, 2023,43(2):136-146.]
[20] Sigler T, Martinus K, Loginova J. Socio-spatial relations observed in the global city network of firms[J]. PloS One, 2021,16(8):e0255461. https://doi.org/10.1371/journal.pone.0255461.
[21] 吴炫,杨家文.流动量与关注度视角下的城市网络结构:以广州、深圳为例[J].地理科学进展,2019,38(12):1843-1853.[Wu Xuan, Yang Jiawen. City network by mobility and attention indices:A comparison of Guangzhou and Shenzhen[J]. Progress in Geography, 2019,38(12):1843-1853.]
[22] Van Nuffel N, Derudder B, Witlox F. Even important connections are not always meaningful:On the use of a polarisation measure in a typology of European cities in air transport networks[J]. Tijdschrift voor Economische en Sociale Geografie, 2010,101(3):333-48.
[23] Neal Z P. Backbone:An R package to extract network backbones[J]. PloS One, 2022, 17(5):e0269137. https://doi.org/10.1371/journal.pone.0269137.
[24] 魏石梅,潘竟虎.中国地级及以上城市网络结构韧性测度[J].地理学报,2021,76(6):1394-1407.[Wei Shimei, Pan Jinghu. Network structure resilience of cities at the prefecture level and above in China[J]. Acta Geographica Sinica, 2021,76(6):1394-1407.]
[25] 戴靓,丁子军,曹湛,等.长三角地区城市协同创新网络的演化特征及其驱动力[J].资源科学,2023,45(5):1006-1019.[Dai Liang, Ding Zijun, Cao Zhan, et al. Change and driving forces of intercity collaborative innovation networks in the Yangtze River Delta region[J]. Resources Science, 2023,45(5):1006-1019.]
[26] Serrano M A, Boguna M, Vespignani A. Extracting the multiscale backbone of complex weighted networks[J]. Proceedings of the National Academy of Sciences, 2009,106(16):6483-6488.
[27] 王鹏飞,李红波.基于产业结构关联视角的区域经济韧性作用机理研究:以江苏省为例[J].地理科学进展,2022,41(2):224-238.[Wang Pengfei, Li Hongbo. Mechanism of regional economic resilience from the perspective of industrial structure relevance:Taking Jiangsu province as an example[J]. Progress in Geography, 2022, 41(2):224-238.]
[28] Zhang W, Chong Z, Li X, et al. Spatial patterns and determinant factors of population flow networks in China:Analysis on Tencent location big data[J]. Cities, 2020, 99:102640. http://doi.org/10.1016/j.cities.2020.102640.
[29] 周建平,刘程军,徐维祥,等.电子商务背景下快递企业物流网络结构及自组织效应:以中通快递为例[J].经济地理,2021,41(2):103-112.[Zhou Jianping, Liu Chengjun, Xu Weixiang, et al. Logistics network structure of express delivery companies and their selforganization effect under the background of e-commerce:Taking ZTO express as an example[J]. Economic Geography, 2021,41(2):103-112.]
[30] 桂钦昌,杜德斌,刘承良,等.基于随机行动者模型的全球科学合作网络演化研究[J].地理研究,2022,41(10):2631-2647.[Gui Qinchang, Du Debin, Liu Chengliang, et al. The evolution of the global scientific collaboration network:A stochastic actor-oriented model approach[J]. Geographical Research, 2022,41(10):2631-2647.]
[31] Broekel T, Balland P A, Burger M, et al. Modeling knowledge networks in economic geography:A discussion of four methods[J]. The Annals of Regional Science, 2014,53:423-452.
[32] 韩刚,史修松,刘志敏.基于ERGM模型的江苏省城市网络紧凑性形成机理研究[J].地理科学进展,2021,40(12):2025-2034.[Han Gang, Shi Xiusong, Liu Zhimin. Formation mechanism of network compactness in Jiangsu province based on exponential random graph models[J]. Progress in Geography, 2021,40(12):2025-2034.]
[33] Wang B, Loo B P. The hierarchy of cities in Internet news media and Internet search:Some insights from China[J]. Cities, 2019,84:121-133.
[34] 安俞静,刘静玉,乔墩墩.中原城市群城市空间联系网络格局分析:基于综合交通信息流[J].地理科学,2019,39(12):1929-1937.[An Yujing, Liu Jingyu, Qiao Dundun. Urban spatial connection and network structure in Zhongyuan urban agglomeration:A study based on integrated traffic and information flow[J]. Scientia Geographica Sinica, 2019,39(12):1929-1937.]
[35] Van der Pol J. Introduction to network modeling using Exponential Random Graph Models (ERGM):Theory and an application using R-project[J]. Computational Economics, 2019,54:845-875.
[36] 罗超亮,刘冰,姜晖."谁"在投资中国文旅创业板块:基于"领投-跟投"关系的研究[J].旅游学刊,2023,38(1):66-80.[Luo Chaoliang, Liu Bing, Jiang Hui. "Who" invests in new culture and tourism ventures in China? A study on "leader-follower" relationships in venture capital syndication[J]. Tourism Tribune, 2023,38(1):66-80.]