城市实体特征对城市网络空间影响力的作用机制——基于互联网新闻媒体的分析

doi:10.13249/j.cnki.sgs.2017.08.001

摘要/Abstract

摘要：

借助百度新闻媒体指数功能,收集281个地级市或以上城市在2011~2014年间的媒体指数,分析基于互联网新闻媒体的城市网络空间影响力差异及其变化。其次,通过对面板数据的回归分析,从政府因素与市场因素两个方面探讨城市在实体空间中的特征（或传统影响力）是如何作用到城市在网络空间中的影响力。并且,通过对各年数据的回归分析,进一步考察政府因素与市场因素作用机制的演化过程。

关键词: 城市网络空间影响力, 政府因素, 市场因素, 互联网新闻媒体, 大数据

Abstract:

Along with the rapid development of information and communication technologies, the Internet has functioned as an important news media in people’s day-to-day lives. As the centers of flows of people, goods, information, and capital, cities have been frequently appeared in the Internet news media. However, the number of reports about city in the Internet news media is not evenly distributed for every city; instead, the distribution shows huge gaps among cities and reveal the disparity among city’s importance in the Internet. By collecting and analyzing the yearly Media Index of 281 prefectural-level and above cities in Baidu, the most popular search engine website in China, this current study firstly analyzed city’s importance and its changes in the period 2011-2014. By adopting panel data regression model this study then explained how the importance of cities in the Internet is related to its characteristics in government and market perspectives. Finally, the evolution of the influence power of government and market factors was explored from the regression model results of each year. The main conclusions can be addressed as follows. 1) There are huge gaps in the amount of coverage of cities in the Internet news media, exhibiting obvious hierarchical and spatial variation of city’s importance in the Internet. However, both variations constantly and gradually dropped in the period 2011-2014. 2) The amount of coverage of cities in the Internet news media has been heavily determined by the city’s government factor (i.e., city’s status in the hierarchical administration system) and market factor including population size, economic development performance, tourism resource, and the spatial distance from the national media center. Specifically, our panel data regression model shows that provincial-level city, city with a larger population size, a larger GDP per capita, being a national-level historical and cultural city, a closer distance from Beijing (the national media center) tends to have more chances to be reported in the Internet news media. 3) Interestingly, through regression models on the impacts of the abovementioned variable of each year, results demonstrate that the impact of government factor decreased while that of market factor increased, indicating the role of Internet in promoting economic growth in government’s recent development strategy.

Key words: city’, s power in the internet, government factor, market factor, internet news media, big data

中图分类号:

K901

王波, 甄峰. 城市实体特征对城市网络空间影响力的作用机制——基于互联网新闻媒体的分析[J]. 地理科学, 2017, 37(8): 1127-1134.

Bo Wang, Feng Zhen. Impacts of City’s Characteristics on City’s Importance in the Virtual World: An Empirical Analysis Based on Internet News Media[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(8): 1127-1134.

图/表 4

表1

表2

表3

表4

参考文献 37

[1]	Friedmann J.The world city hypothesis[J]. Development andChange, 1986, 17(1): 69-83. doi: 10.1111/dech.1986.17.issue-1
[2]	Chen X.China's city hierarchy, urban policy and spatial development in the 1980s[J]. Urban Studies, 1991, 28(3): 341-367. doi: 10.1080/00420989120080391
[3]	顾朝林. 中国城镇体系: 历史·现状·展望[M]. 北京:商务印书馆, 1992.
	[Gu Chaolin.China urban System: History·Today·Future. Beijing: The Commercial Press, 1992.]
[4]	许学强, 程玉鸿. 珠江三角洲城市群的城市竞争力时空演变[J]. 地理科学, 2006, 26(3): 257-265. doi: 10.3969/j.issn.1000-0690.2006.03.001
	[Xu Xueqiang, Cheng Yuhong.Spatial temporal changes of urban competitiveness in urban cluster of Pearl River Delta. Scientia Geographica Sinica, 2006, 26(3): 257-265.] doi: 10.3969/j.issn.1000-0690.2006.03.001
[5]	陈刚强, 李郇, 许学强. 中国城市人口的空间集聚特征与规律分析[J]. 地理学报, 2008, 63(10): 1045-1054.
	[Chen Gangqiang, Li Xun, Xu Xueqiang.Spatial agglomeration and evolution of urban population in China. Acta Geographica Sinica, 2008, 63(10): 1045-1054.]
[6]	程开明, 庄燕杰. 城市体系为序-规模特征的空间计量分析——以中部地区地级以上城市为例[J]. 地理科学, 2012, 32(8): 905-912.
	[Cheng Kaiming, Zhuang Yanjie.Spatial econometric analysis of the rank-size rule for urban system: a case of prefectural-level cities in China’s Middle Area. Scientia Geographica Sinica, 2012, 32(8): 905-912.]
[7]	Castells M.The rise of the network society: The information age: Economy, society, and culture[M]. New York: John Wiley & Sons, 2011.
[8]	Taylor P J, Hoyler M, Verbruggen R.External urban relational process: introducing central flow theory to complement central place theory[J]. Urban studies, 2010, 47(13): 2803-2818. doi: 10.1177/0042098010377367
[9]	Beaverstock J V, Smith R G, Taylor P J et al. Globalization and world cities: some measurement methodologies[J]. Applied Geography, 2000, 20(1): 43-63. doi: 10.1016/S0143-6228(99)00016-8
[10]	Godfrey B J, Zhou Y.Ranking world cities: multinational corporations and the global urban hierarchy[J]. Urban Geography, 1999, 20(3): 268-281. doi: 10.2747/0272-3638.20.3.268
[11]	Zook M A.Old hierarchies or new networks of centrality? The global geography of the Internet content market[J]. American Behavioral Scientist, 2001, 44(10): 1679-1696. doi: 10.1177/00027640121958113
[12]	莫辉辉, 金凤君, 刘毅, 等. 机场体系中心性的网络分析方法与实证[J]. 地理科学, 2010, 30(2): 204-212.
	[Mo Huihui, Jin Fengjun, Liu Yiet al. Network analysis on centrality of airport system. Scientia Geographica Sinica, 2010, 30(2): 204-212.]
[13]	董超, 修春亮, 魏冶. 基于通信流的吉林省流空间网络格局[J]. 地理学报, 2014, 69(4): 510-519. doi: 10.11821/dlxb201404007
	[Dong Chao, Xiu Chunliang, Wei Ye.Network structure of ‘space of flows’ in Jilin province based on telecommunication flows. Acta Geographica Sinica, 2014, 69(4): 510-519.] doi: 10.11821/dlxb201404007
[14]	甄峰, 王波, 陈映雪. 基于网络社会空间的中国城市网络特征——以新浪微博为例[J]. 地理学报, 2012, 67(8): 1031-1043. doi: 10.1007/s11783-011-0280-z
	[Zhen Feng, Wang Bo, Chen Yingxue.China’s city network characteristics based on social network space: An empirical analysis of Sina micro-blog. Acta Geographica Sinica, 2012, 67(8): 1031-1043.] doi: 10.1007/s11783-011-0280-z
[15]	汪明峰, 宁越敏. 互联网与中国信息网络城市的崛起[J]. 地理学报, 2010, 59(3): 446-454.
	[Wang Mingfeng, Ning Yuemin.The Internet and the rise of information network cities in China. Acta Geographica Sinica, 2010, 59(3): 446-454.]
[16]	Zhen F, Wang B, Wei Z.The rise of the internet city in China: Production and consumption of internet information[J]. Urban Studies, 2015, 52(13): 2313-2329. doi: 10.1177/0042098014547369
[17]	刘瑜. 社会感知视角下的若干人文地理学基本问题再思考[J]. 地理学报, 2016, 71(4): 564-575. doi: 10.11821/dlxb201604003
	[Liu Yu.Revisiting several basic geographical concepts: A social sensing perspective. Acta Geographica Sinica, 2016, 71(4): 564-575.] doi: 10.11821/dlxb201604003
[18]	甄峰, 王波. “大数据” 热潮下人文地理学研究的再思考[J]. 地理研究, 2015, 34(5): 803-811. doi: 10.11821/dlyj201505001
	[Zhen Feng, Wang Bo.Rethinking human geography in the age of big data. Geographical Research, 2015, 34(5): 803-811.] doi: 10.11821/dlyj201505001
[19]	Pred A.Urban growth and city systems in the United States, 1840-1860[M]. Boston: Harvard University Press, 1980.
[20]	Taylor P J.Hierarchical tendencies amongst world cities: A global research proposal[J]. Cities, 1997, 14(6): 323-332. doi: 10.1016/S0264-2751(97)00023-1
[21]	Avraham E.Cities and their news media images[J]. Cities, 2000, 17(5): 363-370. doi: 10.1016/S0264-2751(00)00032-9
[22]	Avraham E.Media strategies for improving an unfavorable city image[J]. Cities, 2004, 21(6): 471-479. doi: 10.1016/j.cities.2004.08.005
[23]	Hachigian N.China's cyber-strategy[J]. Foreign Affairs New York, 2001, 80(2): 118-133. doi: 10.2307/20050069
[24]	Beriatos E, Gospodini A.“Globalizing” urban landscapes: Athens and the 2004 Olympics[J]. Cities, 2004, 21(3): 187-202. doi: 10.1016/j.cities.2004.03.004
[25]	张京祥, 王旭. 内生型城市营销推动下的城市尺度跃迁——基于盱眙的实证研究[J]. 城市规划学刊, 2012, 2: 33-38. doi: 10.3969/j.issn.1000-3363.2012.02.005
	[Zhang Jingxiang, Wang Xu.The scaling up of cities in the process of endogenous city marketing —A case study of Xuyi County. Urban Planning Forum, 2012, 2: 33-38.] doi: 10.3969/j.issn.1000-3363.2012.02.005
[26]	The UCLA Internet report: Surveying the digital future[R]. Los Angeles: UCLA Center for Communication Policy, 2000.
[27]	Hill L L.Georeferencing: The geographic associations of information[M]. Boston: Mit Press, 2009.
[28]	Yuan Q, Nsoesie E O, Lv B et al. Monitoring influenza epidemics in china with search query from baidu[J]. PloS one, 2013, 8(5): e64323. doi: 10.1371/journal.pone.0064323 pmid: 23750192
[29]	Zhang W, Shen D, Zhang Y et al. Open source information, investor attention, and asset pricing[J]. Economic Modelling, 2013, 33: 613-619. doi: 10.1016/j.econmod.2013.03.018
[30]	刘铮, 王世福, 赵渺希, 等. 有向加权型城市网络的探索性分析[J]. 地理研究, 2013, 32(7): 1253-1268.
	[Liu Zheng, Wang Shifu,Zhao Miaoxiet al. Exploratory analysis of directed weighted network of city. Geographical Research, 2013, 32(7): 1253-1268.]
[31]	王波, 甄峰. 互联网下的中国城市等级体系及其作用机制——基于百度搜索的实证分析[J]. 经济地理, 2016, 36(1): 46-52.
	[Wang Bo, Zhen Feng.China’s city hierarchy under Internet and its influencing mechanism: An empirical analysis based on Baidu Search. Economic Geography, 2016, 36(1): 46-52.]
[32]	Schmetterer L.Introduction to mathematical statistics[M]. Berlin: Springer Science & Business Media, 2012.
[33]	国家统计局. 中国城市统计年鉴[M]. 北京: 中国统计出版社, 2011-2015.
	[National Bureau of Statistics of China. China City Statistical Yearbook. Beijing:China Statistics Press, 2011-2015.]
[34]	White H.A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity[J]. Econometrica: Journal of the Econometric Society, 1980: 817-838.
[35]	Graham M.Geography/internet: ethereal alternate dimensions of cyberspace or grounded augmented realities?[J]. The Geographical Journal, 2013, 179(2): 177-182. doi: 10.1111/geoj.12009
[36]	Wang B, Zhen F,Wei Z et al. A theoretical framework and methodology for urban activity spatial structure in e-society: Empirical evidence for Nanjing City, China[J]. Chinese Geographical Science, 2015, 25(6): 672-683. doi: 10.1007/s11769-015-0751-4
[37]	王波, 甄峰. 南京市区活动空间总体特征研究——基于大数据的实证分析[J]. 人文地理, 2014, 29(3): 14-21, 55.
	[Wang Bo, Zhen Feng.The research on characteristics of urban activity space in Nanjing: An empirical analysis based on big data. Human Geography, 2014, 29(3): 14-21, 55.]

变量		定义
因变量	M_it	城市i在年份t的媒体指数中位数值（i = 1, 2, 3…281; t = 2011, 2012, 2013, 2014）,衡量城市的网络空间影响力
自变量	G_i	虚拟变量,当城市i是省级市时,G_i=1;否则,G_i =0
	P_i₍_t-₁₎	城市i在年份(t-1)的常住人口规模
	E_i₍_t-₁₎	城市i在年份(t-1)的人均国内生产总值
	T_i₍_t-₁₎	虚拟变量,当城市i在年份(t-1)是全国历史文化名城时,T_i₍_t-₁₎ =1;否则,T_i₍_t-₁₎ =0
	D_iBJ	城市i与北京的直线空间距离。当i = Beijing时, lnD_iBJ =0

城市^a	2011年			2012年		2013年			2014年
城市^a	M		排名		M	排名	M	排名	M	排名
北京	3666.0	1		4094.0	1	3744.0	1		2745.0	1
上海	2610.0	2		2574.0	2	2642.0	2		1423.0	2
天津	1246.0	3		1398.0	4	1163.0	8		734.0	10
广州	1170.0	4		1428.0	3	1737.0	3		1025.5	3
重庆	1117.0	5		1108.0	5	1302.0	6		911.5	5
深圳	1024.0	6		1105.0	6	1251.0	7		847.5	7
成都	773.0	7		761.0	9	1081.0	9		890.5	6
武汉	752.0	8		980.0	8	1357.0	5		734.0	9
南京	634.0	9		1002.0	7	1479.0	4		932.0	4
杭州	584.0	10		652.0	11	982.0	10		749.5	8
沈阳	500.0	11		486.0	17	717.0	17		596.0	13
青岛	474.0	12		677.0	10	935.0	11		572.0	16
西安	458.0	13		567.0	12	900.0	12		688.0	11
济南	449.0	14		533.0	15	781.0	14		578.5	15
郑州	448.0	15		556.0	13	866.0	13		660.0	12
合肥	385.0	16		493.0	16	729.0	16		523.5	17
长沙	338.0	17		554.0	14	768.0	15		583.5	14
大连	349.0	18		348.0	20	523.0	20		364.5	29
宁波	328.0	19		384.0	19	543.0	18		410.0	22
昆明	309.0	20		330.0	21	514.0	21		421.5	21

变量	政府因素			市场因素			综合
变量	系数		S.E.		系数	S.E.	系数	S.E.
G_i (地级市作参照值)
省级市	2.767***	0.205					1.427***	0.145
Ln P_i₍_t_-1)				1.081***	0.068		0.907***	0.063
Ln E_i₍_t_-1)				0.956***	0.074		0.815***	0.069
T_i₍_t_-1)				0.547***	0.091		0.367***	0.085
Ln D_i_BJ				-0.108*	0.064		-0.125**	0.056
常数	2.896***		-12.309***			-9.850***
年度虚拟变量	包含		包含			包含
N	1124		1124			1124
Overall R²	0.399		0.699			0.759
Wald chi²	983.57***		1334.59***			1641.41***

变量	2011			2012			2013			2014
变量	系数		S.E.		系数		S.E.	系数	S.E.	系数	S.E.
G_i (地级市作为参照值)
省级市	1.647***	0.136		1.383***	0.133		1.216***	0.163		0.923***	0.159
Ln P_i₍_t_-1)	0.875***	0.060		0.970***	0.059		1.134***	0.072		1.145***	0.071
Ln E_i₍_t_-1)	0.878***	0.067		0.958***	0.069		1.062***	0.087		1.027***	0.084
T_i₍_t_-1)	0.280***	0.092		0.274***	0.090		0.389***	0.109		0.402***	0.106
Ln D_i_BJ	-0.096*	0.052		-0.106**	0.051		-0.182***	0.062		-0.131**	0.060
常数	-10.536***		-11.677***			-13.022***		-13.223***
N	281		281			281		281
Adj. R²	0.793		0.797			0.763		0.752
F	215.11***		220.40***			181.09***		170.96***