Analysis on the evolution characteristics and driving factors of urban information network structure in China

doi:10.3969/j.issn.1004-9479.2020.04.2019284

Abstract

Abstract:

Information flow can objectively reflect the social and economic linkages of cities, and is of great value to the study of urban networks. Based on the 2011, 2014 and 2017 intercity information attention data, we analyze the evolution characteristics and driving factors of urban network structure in China from the aspects of network density, centrality, urban linkages by the social network analysis method. It shows that:1) The structure of urban information network has been significantly expanded, but the overall strength of the network linkages is still low. The strength of urban linkages within provinces is far higher than that of cross-region, it is still heavily influenced by administrative territorial entity.2) The centrality of information network nodes has been significantly improved. The hot spots are mainly concentrated in the three major urban agglomerations along the eastern seaboard. Some central and western regional core cities such as Chongqing, Chengdu and Zhengzhou have grown into national core cities, but there is still a big gap between the mid-western and the eastern region of information development.3) The hierarchical distribution of urban information network is obvious, and it presents the characteristics of local area close connection and regional integration. The core network evolved from "axis-spoke" structure with Beijing and Shanghai as its core to a diamond structure with Beijing-Shanghai-Guangzhou,Shenzhen-Chengdu, Chongqing as its core.4) Complementary factors such as information level, the basis of economic development, urban functions, and the intervening factors of network marketing, and big event effect, as well as high-efficiency factors such as information technology reform, urban agglomeration construction are interacted to promote the optimization and reorganization of information network structure.

Key words: Baidu index, social network analysis, urban information network, structural evolution, driving factors

摘要：

信息流能够客观反映城市社会经济联系，对城市网络研究具有重要价值。基于2011、2014和2017年中国城市间信息关注度数据，利用社会网络分析法，从网络密度、中心度、城市联系等方面分析中国城市网络结构的演变特征及其驱动因素，研究表明：1）城市信息网络结构明显拓展但网络总体联系强度仍较低；省域内部信息联系强度高于跨区域联系，信息联系仍受行政区划的影响较大。2）网络节点中心度显著提高，热点区主要集中在东部沿海三大城市群；中西部部分区域核心城市如重庆、成都、郑州等成长为全国性核心城市，但中西部地区城市信息发展仍与东部地区差距较大。3）信息联系层级分布特征明显，并呈现局部区域联系紧密、区域一体化特征；核心网络由以北京、上海为核心的“轴-辐”结构演变为以“北京-上海-广深-成渝”为核心的“菱形”结构。4）信息化水平、经济发展基础、城市职能等互补性因素，网络营销、大事件效应等介入性因素及信息技术变革、城市群建设等高效性因素相互作用，共同促进信息网络结构优化重组。

关键词: 百度指数, 社会网络分析, 城市信息网络, 结构演变, 驱动因素

Dawei MEI, Chunliang XIU, Xinghua FENG. Analysis on the evolution characteristics and driving factors of urban information network structure in China[J]. World Regional Studies, 2020, 29(4): 717-727.

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.

Figures/Tables 5

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2011年	城市	2014年	城市	2017年	城市
第一层级（核心城市）	北京、上海等2个城市	第一层级（核心城市）	北京、上海、广州、深圳、郑州、杭州等6个城市	第一层级（核心城市）	北京、上海、杭州、深圳、广州、郑州、成都、重庆等8个城市
第二层级（次核心城市）	合肥、重庆、福州、泉州、厦门、广州、深圳、佛山、惠州等57个城市	第二层级（次核心城市）	合肥、重庆、福州、泉州、厦门、佛山、惠州等47个城市	第二层级（次核心城市）	合肥、重庆、福州、郑州、泉州、厦门、佛山等41个城市
第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等281个城市	第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等287个城市	第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等291个城市

2011年	城市	2014年	城市	2017年	城市
第一层级（核心城市）	北京、上海等2个城市	第一层级（核心城市）	北京、上海、广州、深圳、郑州、杭州等6个城市	第一层级（核心城市）	北京、上海、杭州、深圳、广州、郑州、成都、重庆等8个城市
第二层级（次核心城市）	合肥、重庆、福州、泉州、厦门、广州、深圳、佛山、惠州等57个城市	第二层级（次核心城市）	合肥、重庆、福州、泉州、厦门、佛山、惠州等47个城市	第二层级（次核心城市）	合肥、重庆、福州、郑州、泉州、厦门、佛山等41个城市
第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等281个城市	第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等287个城市	第三层级（边缘城市）	滁州、宿州、安庆、六安、蚌埠、亳州、阜阳、芜湖、宣城等291个城市

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