Detection of meso-scale structure characteristics of the central plains urban agglomeration based on the network built from toponym co-occurrences in the news

doi:10.13474/j.cnki.11-2246.2021.343

Abstract

Abstract: In this study, the central plains urban agglomeration (CPUA) is selected as the study area to construct a city network using toponym co-occurrence in the news. Furthermore, a method framework is proposed to detect community structure and core-peripheral structure of the resultant network. The following findings are obtained:① The CPUA are divided into 5 communities and the provincial boundary has played a major role in hindering the interaction between cities in virtual cyberspace. ② In the core-periphery structure composed of cities in Henan province, the identified core cities are distributed in an oblique "L" shape around Zhengzhou.③The central position of Zhengzhou is more prominent, while Luoyang's sub-center status is not obvious, and the overall multi-center level of CPUA is relatively low. Based on the above findings, suggestions are given from regional planning and urban role positioning for the integration of cities within the CPUA.

Key words: central plains urban agglomeration, city network, toponym co-occurrences, community structure, core-peripheral structure

CLC Number:

P208

YUE Hanqiu, WANG Qi, LU Di, LI Yuliang. Detection of meso-scale structure characteristics of the central plains urban agglomeration based on the network built from toponym co-occurrences in the news[J]. Bulletin of Surveying and Mapping, 2021, 0(11): 81-86.

References

[1] 高玉祥, 韩峰, 段晓峰. "一带一路"节点城市群轨道交通空间布局分析——以兰州-西宁城市群为例[J]. 测绘通报, 2018(12):114-118.
[2] 方创琳. 中国新型城镇化高质量发展的规律性与重点方向[J]. 地理研究, 2019, 38(1):13-22.
[3] 李茜铭, 郑伯红, 熊羽军. 基于夜间灯光遥感数据的环洞庭湖生态经济区城市群时空扩展[J]. 经济地理, 2021, 41(2):92-102.
[4] 韩剑萍, 黄庆旭, 何春阳, 等. 基于位序钟的成渝城市群城市位序——规模动态分析[J]. 经济地理, 2020, 40(12):48-55.
[5] 宁晓刚, 王浩, 林祥国, 等. 京津冀城市群1990-2015年城区时空扩展监测与分析[J]. 测绘学报, 2018, 47(9):1207-1215.
[6] 许正森, 徐永明. 整合DMSP/OLS和NPP/VIIRS夜间灯光遥感数据的长江三角洲城市格局时空演化研究[J]. 地球信息科学学报, 2021, 23(5):837-849.
[7] CASTELLS M. The rise of the network society[M]. Malden:Blackwell Publishers, 1996.
[8] CASTELLS M. Globalisation, networking, urbanisation:reflections on the spatial dynamics of the information age[J]. Urban Studies, 2010, 47(13):2737-2745.
[9] BATTY M. The new science of cities[M]. Cambridge:MIT Press, 2013.
[10] 马学广, 李鲁奇. 中国城市网络化空间联系结构——基于银行网点数据的研究[J]. 地理科学进展, 2017, 36(4):393-403.
[11] HU X, WANG C, WU J, et al. Understanding interurban networks from a multiplexity perspective[J]. Cities, 2020, 99:102625.
[12] LIU Y, WANG F, KANG C, et al. Analyzing relatedness by toponym co-occurrences on web page[J]. Transactions in GIS, 2014, 18(1):89-107.
[13] 胡定利, 李锐, 孟瑶, 等. 新闻地名共现视角下的中国城市网络[J]. 武汉大学学报(信息科学版), 2020, 45(2):281-288.
[14] BOCCALETTI S, LATORA V, MORENO Y, et al. Complex networks:structure and dynamics[J]. Physics Reports, 2006, 424(4/5):175-308.
[15] 王录仓, 刘海洋, 刘清. 基于腾讯迁徙大数据的中国城市网络研究[J]. 地理学报, 2021, 76(4):853-869.
[16] FORTUNATO S. Community detection in graphs[J]. Physics Reports, 2010, 486(3/4/5):75-174.
[17] YUE H, GUAN Q, PAN Y,et al. Detecting clusters over intercity transportation networks using K-shortest paths and hierarchical clustering:a case study of mainland China[J]. International Journal of Geographical Information Science, 2019, 33(5):1082-1105.
[18] 刘正兵, 刘静玉, 何孝沛, 等. 中原经济区城市空间联系及其网络格局分析——基于城际客运流[J]. 经济地理, 2014, 34(7):58-66.
[19] KOJAKU S, MASUDA N. Finding multiple core-periphery pairs in networks[J]. Physical Review E, 2017, 96(5):052313.
[20] ROSVALL M, BERGSTROM C T. An information-theoretic framework for resolving community structure in complex networks[J]. Proceedings of the National Academy of Sciences, 2007, 104(18):7327-7331.
[21] ROSVALL M, BERGSTROM C T. Maps of random walks on complex networks reveal community structure[J]. Proceedings of the National Academy of Sciences, 2008, 105(4):1118-1123.
[22] RAGHAVAN U N, ALBERT R, KUMARA S. Near linear time algorithm to detect community structures in large-scale networks[J]. Physical Review E, 2007, 76(3):036106.
[23] 刘瑜, 龚俐, 童庆禧. 空间交互作用中的距离影响及定量分析[J]. 北京大学学报(自然科学版), 2014, 50(3):526-534.
[24] GREEN N. Functional polycentricity:a formal definition in terms of social network analysis[J]. Urban Studies, 2007, 44(11):2077-2103.
[25] LIU X, DERUDDER B, WU K. Measuring polycentric urban development in China:an intercity transportation network perspective[J]. Regional Studies, 2016, 50(8):1302-1315.