全球留学生留学网络时空演化及其影响因素

doi:10.11821/dlxb202004002

Abstract

Abstract:

Based on the data released by UNESCO on international student mobility in tertiary education from 2001 to 2015, this paper draws on network science to construct a multidimensional weighted directed network heterogeneity model. This model combines the GIS spatial analysis method and the negative binomial regression model to study spatiotemporal evolution and factors influencing international student mobility networks. The results are as follows. First, in terms of the evolutionary characteristics of time series, the linkages of international student mobility networks have increased from 4921 to 9137, and its average weighted degree centrality has rapidly increased from 8004 to 20,834, which indicates that both the number of international students and the choices of overseas routines are mounting. Second, in terms of the topological structure, it has evolved from a single core comprising the United States into dual cores comprising the United States and China. Gradually, Asian countries have become the main body of international student mobility networks, while the centrality of European countries has reduced. Thirdly, in terms of spatial structure, the international student mobility network has a significant core-periphery structure and hierarchical characteristics. The countries in the core, strong semi-periphery and semi-periphery alternate with countries from other tiers. The spatial patterns of the international student mobility network "from east to west, and from south to north" are changing. China and Australia have become the new regional centers of international student mobility networks, meaning that regionalization has become an important trend. Finally, regression analysis shows that the flow of international students correlates positively with the quality of higher education in destination countries, the number of students in colleges and universities, the per capita GDP, the historical links connection between the destination country and the country of origin, and the level of globalization. Geographical distance and linguistic proximity have a significant negative correlation with the flow of international students, indicating that the impediment of language is rapidly weakening, while geographical distance still hinders student mobility.

Key words: international students, international talent mobility, network structure, geospace

HOU Chunguang, DU Debin, LIU Chengliang, GUI Qinchang, LIU Shufeng, QIN Xionghe. Spatio-temporal evolution and factors influencing international student mobility networks in the world[J].Acta Geographica Sinica, 2020, 75(4): 681-694.

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References 34

[1]	Du Debin . Global Science and Technology Innovation Center: Power and Model. Shanghai: Shanghai People's Press, 2015.
	[ 杜德斌 . 全球科技创新中心动力与模式. 上海: 上海人民出版社, 2015.]
[2]	Du Debin, Feng Chunping, Li Tongsheng , et al. World Economic Geography. Beijing: Higher Education Press, 2009.
	[ 杜德斌, 冯春萍, 李同升 , 等. 世界经济地理. 北京: 高等教育出版社, 2009.]
[3]	Macrander A . Fractal inequality: A social network analysis of global and regional international student mobility. Research in Comparative & International Education, 2017,12(2):243-268.
[4]	Perkins R, Neumayer E . Geographies of educational mobilities: Exploring the uneven flows of international students. Geographical Journal, 2014,180(3):246-259. doi: 10.1111/geoj.12045
[5]	Börjesson M . The global space of international students in 2010. Journal of Ethnic & Migration Studies, 2017,43(8):1256-1275.
[6]	Barnett G A, Wu R Y . The international student exchange network: 1970 & 1989. Higher Education, 1995,30(4):353-368. doi: 10.1007/BF01383539
[7]	Hou Chunguang, Du Debin, Liu Chengliang , et al. Spatiotemporal evolution of global talent mobility network based on the data of international student mobility. Geographical Research, 2019,38(8):1862-1876.
	[ 侯纯光, 杜德斌, 刘承良 , 等. 全球人才流动网络复杂性的时空演化: 基于全球高校留学生流动数据. 地理研究, 2019,38(8):1862-1876.]
[8]	Eric Sheppard, Trevor Barnes, Ash Amin , et al. A Companion to Economic Geography. Tang Maolin, Tan Jinghua, Li Jiangtao, et al., trans. Beijing: The Commercial Press, 2008.
	[ 埃里克·谢波德, 特雷弗·巴恩斯, 阿什·阿明 , 等. 经济地理学指南. 汤茂林, 谈静华, 李江涛, 等, 译. 北京: 商务印书馆, 2008.]
[9]	Hou Chunguang, Du Debin, Duan Dezhong , et al. The evolution of the network structure of talent mobility in countries or regions along the "Belt and Road". Scientia Geographica Sinica, 2019,39(11):1711-1718.
	[ 侯纯光, 杜德斌, 段德忠 , 等. “一带一路”沿线国家或地区人才流动网络结构演化. 地理科学, 2019,39(11):1711-1718.]
[10]	Zhang Kangzhi, Zhang Tong . The concept of core-periphery in the world-system analysis. Journal of Renmin University of China, 2015,29(2):80-89.
	[ 张康之, 张桐 . “世界体系论”的“中心—边缘”概念考察. 中国人民大学学报, 2015,29(2):80-89.]
[11]	Richard Peet . Modern Geographical Thought. Zhou Shangyi, trans. Beijing: The Commercial Press, 2007.
	[ 理查德·皮特 . 现代地理学思想. 周尚意, 译. 北京: 商务印书馆, 2007.]
[12]	Miao Changhong, Wei Yehua, Lyu Lachang . New Economic Geographies. Beijing: Science Press, 2011.
	[ 苗长虹, 魏也华, 吕拉昌 . 新经济地理学. 北京: 科学出版社, 2011.]
[13]	Wang Zheng, Xia Haibin, Wu Jing , et al. General Geography. Beijing: Science Press, 2010.
	[ 王铮, 夏海斌, 吴静 . 普通地理学. 北京: 科学出版社, 2010.]
[14]	Liu Jun. Lectures on Whole Network Approach. Shanghai: Shanghai People's Publishing House, 2014.
	[ 刘军 , 整体网络分析. 上海: 上海人民出版社, 2014.]
[15]	Wang Jiao'e, Mo Huihui, Jin Fengjun . Spatial structural characteristics of Chinese aviation network based on complex network theory. Acta Geographica Sinica, 2009,64(8):899-910. doi: 10.11821/xb200908002
	[ 王姣娥, 莫辉辉, 金凤君 . 中国航空网络空间结构的复杂性. 地理学报, 2009,64(8):899-910.] doi: 10.11821/xb200908002
[16]	Mo Huihui, Wang Jiao'e, Jin Fengjun . Complexity perspectives on transportation network. Progress in Geography, 2008,27(6):112-120. doi: 10.11820/dlkxjz.2008.06.016
	[ 莫辉辉, 王姣娥, 金凤君 . 交通运输网络的复杂性研究. 地理科学进展, 2008,27(6):112-120.] doi: 10.11820/dlkxjz.2008.06.016
[17]	Ducruet C, Cuyala S, Hosni A E . Maritime networks as systems of cities: The long-term interdependencies between global shipping flows and urban development (1890-2010). Journal of Transport Geography, 2018,66(1):340-355. doi: 10.1016/j.jtrangeo.2017.10.019
[18]	Liu Chanjuan, Hu Zhihua . Spatial pattern and complexity of the 21st Century Maritime Silk Road shipping network. World Regional Studies, 2018,27(3):11-18.
	[ 刘婵娟, 胡志华 . “21世纪海上丝绸之路”海运网络空间格局及其复杂性研究. 世界地理研究, 2018,27(3):11-18.]
[19]	Huang Jie, Zhong Yexi, Li Jianxin , et al. Economic accessibility of provincial capital cities in China based on the presence of high-speed rails. Geographical Research, 2016,35(4):757-769. doi: 10.1002/1097-4679(197910)35:4&lt;757::aid-jclp2270350413&gt;3.0.co;2-b pmid: 512000
	[ 黄洁, 钟业喜, 李建新 , 等. 基于高铁网络的中国省会城市经济可达性. 地理研究, 2016,35(4):757-769.] doi: 10.1002/1097-4679(197910)35:4&lt;757::aid-jclp2270350413&gt;3.0.co;2-b pmid: 512000
[20]	Jiang Bo, Chu Nanchen, Xiu Chunliang , et al. Comprehensive evaluation and comparative analysis of accessibility in the four vertical and four horizontal HSR networks in China. Acta Geographica Sinica, 2016,71(4):591-604.
	[ 姜博, 初楠臣, 修春亮 , 等. 中国“四纵四横”高铁网络可达性综合评估与对比. 地理学报, 2016,71(4):591-604.]
[21]	Liu Jinsong . Evolution of world natural gas trade pattern based on social network analysis. Economic Geography, 2016,36(12):89-95.
	[ 刘劲松 . 基于社会网络分析的世界天然气贸易格局演化. 经济地理, 2016,36(12):89-95.]
[22]	Gao Boyang, Li Junwei . The geography of global electric information industry trade network. World Regional Studies, 2017,26(1):1-11.
	[ 高菠阳, 李俊玮 . 全球电子信息产业贸易网络演化特征研究. 世界地理研究, 2017,26(1):1-11.]
[23]	Yang Wenlong, Du Debin, You Xiaojun , et al. Network structure evolution and spatial complexity of global transnational investment. Scientia Geographica Sinica, 2017,37(9):1300-1309.
	[ 杨文龙, 杜德斌, 游小珺 , 等. 世界跨国投资网络结构演化及复杂性研究. 地理科学, 2017,37(9):1300-1309.]
[24]	Liu Chengliang, Gui Qinchang, Duan Dezhong , et al. Structural heterogeneity and proximity mechanism of global scientific collaboration network based on co-authored papers. Acta Geographica Sinica, 2017,72(4):737-752. doi: 10.11821/dlxb201704014
	[ 刘承良, 桂钦昌, 段德忠 , 等. 全球科研论文合作网络的结构异质性及其邻近性机理. 地理学报, 2017,72(4):737-752.] doi: 10.11821/dlxb201704014
[25]	Li Zhenfu, Liang Aimei, Xu Mengqiao . Author network of arctic social science research in China. World Regional Studies, 2018,27(3):30-41.
	[ 李振福, 梁爱梅, 徐梦俏 . 我国北极社会科学研究的作者网络. 世界地理研究, 2018,27(3):30-41.]
[26]	Duan Dezhong, Du Debin, Chen Ying . Technology transfer in China's city system: Process, pattern and influencing factors. Acta Geographica Sinica, 2018,73(4):738-754.
	[ 段德忠, 杜德斌, 谌颖 , 等. 中国城市创新技术转移格局与影响因素. 地理学报, 2018,73(4):738-754.]
[27]	Xian Guo, Zeng Gang, Cao Xianzhong . Structural feature and proximity mechanism of Chinese intercity innovation network. World Regional Studies, 2018,27(5):136-146.
	[ 鲜果, 曾刚, 曹贤忠 . 中国城市间创新网络结构及其邻近性机理. 世界地理研究, 2018,27(5):136-146.]
[28]	Shields R . Globalization and international student mobility: A network analysis. Comparative Education Review, 2013,57(4):609-636. doi: 10.1111/inr.12162 pmid: 25559068
[29]	Kondakci Y, Bedenlier S, Zawacki-Richter O . Social network analysis of international student mobility: Uncovering the rise of regional hubs. Higher Education, 2018,75(1):1-19.
[30]	Barnett G A, Lee M, Ke J , et al. The flow of international students from a macro perspective: A network analysis. Compare A Journal of Comparative & International Education, 2015,46(4):1-27.
[31]	Vögtle E M, Windzio M . Networks of international student mobility: Enlargement and consolidation of the European transnational education space? Higher Education, 2015,72(276):1-19.
[32]	John D. Nystuen, Michael F . Dacey. A graph theory interpretation of nodal regions. Papers of the Regional Science Association, 1961,7(1):29-42.
[33]	Li Xiaojian, Li Guoping, Zeng Gang , et al. Economic Geography. Beijing: Higher Education Press, 2006.
	[ 李小建, 李国平, 曾刚 , 等. 经济地理学. 北京: 高等教育出版社, 2006.]
[34]	Chen T M, Barnett G A . Research on international student flows from a macro perspective: A network analysis of 1985, 1989 and 1995. Higher Education, 2000,39(4):435-453.

年份	网络规模				集聚性	度中心性	强度中心性
年份	节点数	边数	图密度	直径	平均聚类系数	平均度	平均加权度
2001	203	4921	0.120	3	0.686	24	8004
2002	202	5379	0.132	4	0.699	27	10055
2003	205	6021	0.144	4	0.665	29	11206
2004	207	5906	0.139	5	0.670	29	11386
2005	206	5679	0.134	3	0.709	28	11935
2006	207	5959	0.140	4	0.688	29	12068
2007	208	6103	0.142	4	0.708	29	13092
2008	208	6781	0.157	4	0.670	33	14004
2009	208	7026	0.163	4	0.647	34	14993
2010	207	7226	0.169	5	0.674	35	15510
2011	209	7605	0.175	4	0.677	36	16561
2012	211	7793	0.176	5	0.662	37	16631
2013	209	7712	0.177	4	0.687	37	16971
2014	211	8456	0.191	4	0.667	40	18298
2015	212	9137	0.204	3	0.655	43	20834

变量	模型1	模型2	模型3	模型4
目的地国高等教育质量		0.0431^***		0.0469^***
		(0.0027)		(0.0028)
目的地国高校在校生数量		0.0515^***		0.0524^***
		(0.0010)		(0.0010)
目的地国人均GDP		0.1498^***		0.1508^***
		(0.0027)		(0.0027)
语言临近性			-0.6509^***	-0.1589^***
			(0.0343)	(0.0340)
历史联系			0.4406^***	0.7994^***
			(0.0424)	(0.0414)
地理距离			-0.7300^***	-0.6092^**
			(0.2271)	(0.2419)
目的地国全球化水平	0.2261^***	0.0035	0.3313^***	0.0321
	(0.0246)	(0.0242)	(0.0256)	(0.0254)
来源国全球化水平	0.1717^***	0.0468^**	0.1588^***	0.0397^**
	(0.0188)	(0.0190)	(0.0179)	(0.0190)
常数项	0.9470^***	0.3582^***	0.9059^***	0.3294^***
	(0.0215)	(0.0235)	(0.0274)	(0.0290)
样本数	27510	27510	27510	27510
关系对	1834	1834	1834	1834
Wald chi2	166.65	12026.53	951.78	12409.43
Prob > chi2	0.0000	0.0000	0.0000	0.0000
Log likelihood	-137976.95	-134414.42	-137644.68	-134242.95

Spatio-temporal evolution and factors influencing international student mobility networks in the world

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