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The Method and Application of Graphic Recognition of the Social Network Structure of Urban Agglomeration

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Abstract

The spatial structure of urban agglomeration is an important branch of economic geography. As far as the current scholars’ research is concerned, the research method of urban agglomeration is relatively simple, and the visual effect of the results is poor. In this paper, the theory of social network analysis is used and the relationship within the urban agglomeration is expressed by using the UCINET6.0 and NETDRAW software. And then, the Urban Agglomeration along the middle reaches of the Yangtze River is taking as the object of empirical research. The Urban Agglomeration along the middle reaches of the Yangtze River, one of the most intensive areas of education in China, undertakes the important mission of building a new growth pole in China. However, the phenomenon of “group instead of cluster” has always been the bottleneck of besetting healthy development of the urban agglomeration, and the cluster effect appears a decreasing trend. This paper uses the modified economic gravity model and social network analysis method and constructs the “three-dimensional” diagnosis model of social network structure of urban agglomeration consisted of the primate city—social network structure density—social network structure intensity. The economic membership grade and centricity of the primate city, social network structure density of the urban agglomeration and coherent subgroup, and the social network structure intensity of the Urban Agglomeration in the middle reaches of the Yangtze River is measured. It demonstrates the spatial structure of the Urban Agglomeration along the middle reaches of the Yangtze River shows the social network structure characteristics of “weak center traction and discrete clusters”, and points out three problems restricting the Urban Agglomeration along the middle reaches of the Yangtze River. With the introduction of new theories, a three-dimensional diagnostic tool of social network structure of urban agglomerations is designed, which provides theoretical support and decision support for solving the problem of “group instead of cluster” in urban agglomeration.

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References

  1. Shimou, Y. (1992). Characteristics, types and spatial distribution of urban agglomerations in China. Urban Problems, 1, 10–15.

  2. Gottmann, J. (2007). Megalopolis: Or the urbanization of the Northeastern Seaboard. Urban Planning International, 33(3), 189.

    Google Scholar 

  3. Yong, Ma., & Jun, L. (2015). Efficiency evaluation of regional industrial ecology of the Yangtze River middle reaches Urban Agglomerations. Economic Geography, 06, 124–129.

    Google Scholar 

  4. Sheng, H., & Chengli, T. (2014). Research on spatial interaction of the Urban Agglomeration in the middle reaches of the Yangtze River. Economic Geography, 04, 46–53.

    Google Scholar 

  5. Liwen, L., Yi, Z., Xiaofan, L., & Yongsheng, L. (2014). City quality evaluation of Yangtze river city group. Resources and Environment in the Yangtze Basin, 10, 1337–1343.

  6. Jing, M., Xiaofan, L., & Hong, Z. (2016). The coordination of urban development quality system in Urban Agglomeration in the middle reaches of the Yangtze River. Economic Geography, 07, 53–61.

  7. Xuesong, L., & Bowen, S. (2013). Regional integration of the yangtze river middle reaches urban agglomerations: Measuring and comparison. Resources and Environment in the Yangtze Basin, 08, 996–1003.

    Google Scholar 

  8. Grabher, G. (2006). Trading routes, bypasses, and risky intersections: Mapping the travels of networks’ between economic sociology and economic geography. Progress in Human Geography, 30, 163–189.

    Article  Google Scholar 

  9. Wal, A. L. J. T., & Boschma, R. A. (2009). Applying social network analysis in economic geography: Framing some key analytic issues. The Annals of Regional Science, 43(3), 739–756.

    Article  Google Scholar 

  10. Gluckler, J. (2013). Knowledge, networks and space: Connectivity and the problem of noninteractive learning. Regional Studies, 47, 880–894.

    Article  Google Scholar 

  11. Gluckler, J., & Panitz, R. (2016). Relational upgrading in global value networks. Journal of Economic Geography, 16, 1161–1185.

    Google Scholar 

  12. Gluckler, J., Lazega, E., & Hammer, I. (2017). Knowledge and networks. Spring Int Publ, 57, 725–735.

    Google Scholar 

  13. Makarem, N. P. (2016). Social networks and regional economic development: The Los Angeles and Bay Area metropolitan regions, 1980–2010. Environment and Planning C: Government and Policy, 34, 91–112.

    Article  Google Scholar 

  14. Jingwei, L., Shuhui, W., & Junzhi, F. (2015). The spatial economic association of city Agglomeration on CAFTA based on the perspective of social network analysis. Scientia Geographica Sinica, 05, 521–528.

    Google Scholar 

  15. Daliang, J., Ye, S., Hang, R., Yingying, C., & Kezhen, Z. (2015). Analyses on the city network characteristics of middle yangtze urban agglomeration based on baidu index. Resources and Environment in the Yangtze Basin, 10, 1654–1664.

    Google Scholar 

  16. Shengyun, W., Chenyang, Z., & Xiaohe, G. (2016). Analysis on spatial network structure’s dynamic evolution of urban agglomerations in the middle Yangtze river basin. Resources and Environment in the Yangtze Basin, 03, 353–364.

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Acknowledgements

Project supported by the National Social Science Foundation of China (Grant Nos. 15ZDC022, 17BGL209);National Natural Science Foundation of China (Grant Nos. 71373199, 71602192, 71703033);MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 15YJC790108, 16YJC630048); Science and technology fund of Hubei Province (2016ADC109); The special task of the humanities and social science research of the Hubei Provincial Education Department (college student work).

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Correspondence to Renyan Mu.

Appendices

Appendix 1

See Table 10.

Table 10 Economic distances results in the agglomeration in middle reaches of the Yangtze River

Appendix 2

See Table 11.

Table 11 External relation results in the agglomeration in middle reaches of the Yangtze River

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Liu, Z., Mu, R., Hu, S. et al. The Method and Application of Graphic Recognition of the Social Network Structure of Urban Agglomeration. Wireless Pers Commun 103, 447–480 (2018). https://doi.org/10.1007/s11277-018-5454-6

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