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A dynamic co-word network-related approach on the evolution of China’s urbanization research

Abstract

In recent years, China’s urbanization has developed very quickly. Many scholars have conducted China’s urbanization research (CUR) and have published a large number of articles. With CUR as a case, we construct the dynamic co-word network to analyze the characteristics of development about the knowledge system (KS). We draw several conclusions from this research. (1) The development of CUR possesses small-world characteristics and scale-free effects. The co-word network of CUR increases significantly to a large-scale network. (2) Betweenness centrality and eigenvector centrality of the dynamic co-word networks positively correlate with node degree. The popular nodes connecting with a large number of topics are also the nodes that occur in the critical paths. The popular keywords in CUR also bridge distant clusters of the related topics. (3) The clustering coefficients indicate that a number of topics with low degrees tend to relate to the adjacent topics more directly to form “conglobation” clusters. The network is a hierarchical clustered structure. The hub keywords play a crucial role in bridging distinct clusters of highly associated keywords and make them form an integrated network. (4) Since 2003, the CUR has begun to develop systematically. From 1998 to 2015, the hotspots in CUR varied diversely, which are highly correlated with social issues and public concerns. (5) We proposed several practical implications on the development of CUR from the dynamic co-word network measures. Beyond the case of CUR’s KS, we hope the versatility of methods in this research also provides enlightenment for other KS studies.

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References

  • Albert, R., & Barabási, A. L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47–97.

    MathSciNet  Article  MATH  Google Scholar 

  • Alexei, V., Romualdo, P. S., & Alessandro, V. (2002). Large-scale topological and dynamical properties of the internet. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 65(6), 104–130.

    Google Scholar 

  • Bai, Y., Jiang, B., Wang, M., et al. (2016). New ecological redline policy (ERP) to secure ecosystem services in China. Land Use Policy, 55, 348–351.

    Article  Google Scholar 

  • Banerjee, T., & Srivastava, R. K. (2011). Assessment of the ambient air quality at the Integrated Industrial Estate-Pantnagar through the air quality index (AQI) and exceedence factor (EF). Asia Pacific Journal of Chemical Engineering, 6(1), 64–70.

    Article  Google Scholar 

  • Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    MathSciNet  Article  MATH  Google Scholar 

  • Bazm, S., Kalantar, S. M., & Mirzaei, M. (2016). Bibliometric mapping and clustering analysis of Iranian papers on reproductive medicine in scopus database (2010–2014). International Journal of Reproductive BioMedicine, 14(6), 371–382.

    Google Scholar 

  • Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205.

    Article  Google Scholar 

  • Chen, C. (2016). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359–377.

    Article  Google Scholar 

  • Chen, X. W., Chen, J. M., Wu, D. S., Xie, Y. J., & Li, J. (2016a). Mapping the research trends by co-word analysis based on keywords from funded project. Procedia Computer Science, 91, 547–555.

    Article  Google Scholar 

  • Chen, A., Zhao, X. F., Yao, L., & Chen, L. D. (2016b). Application of a new integrated landscape index to predict potential urban heat islands. Ecological Indicators, 69, 828–835.

    Article  Google Scholar 

  • Choi, J., & Kang, W. (2014). Themes and trends in Korean educational technology research: A social network analysis of keywords. Procedia: Social and Behavioral Sciences, 131, 171–176.

    Google Scholar 

  • Choi, J., Yi, S., & Lee, K. C. (2011). Analysis of keyword networks in MIS research and implications for predicting knowledge evolution. Information & Management, 48(8), 371–381.

    Article  Google Scholar 

  • Cohen, B. (2006). Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability. Technology in Society, 28(1–2), 63–80.

    Article  Google Scholar 

  • Erdős, P., & Rényi, A. (1959). On random graphs. Publ. Math, 6, 290–297.

    MathSciNet  MATH  Google Scholar 

  • Fung, J. C. H., Lau, A. K. H., Lam, J. S. L., & Yuan, Z. (2005). Observational and modeling analysis of a severe air pollution episode in western Hong Kong. Journal of Geophysical Research: Atmospheres, 110(9), 1–15.

    Google Scholar 

  • Gu, C. L., Hu, L. Q., Zhang, X. M., et al. (2011). Climate change and urbanization in the Yangtze River Delta. Habitat International, 35(4), 544–552.

    Article  Google Scholar 

  • He, Q. (1999). Knowledge discovery through co-word analysis. Library Trends, 48(1), 133–159.

    Google Scholar 

  • Hu, X. F., Zhao, J., Zha, S. P., Lu, F., & Wang, X. F. (2015). An analysis of the evolution of topics and future trends in ecological security research. Shengtai Xuebao/Acta Ecologica Sinica, 35(21), 6934–6946.

    Google Scholar 

  • Karakus, C. B., Cerit, O., & Kavak, K. S. (2015). Determination of land use/cover changes and land use potentials of Sivas city and its surroundings using Geographical Information Systems (GIS) and Remote Sensing (RS). Procedia Earth and Planetary Science, 15, 454–461.

    Article  Google Scholar 

  • Lin, Y., Hao, P., & Geertman, S. (2015). A conceptual framework on modes of governance for the regeneration of Chinese ‘villages in the city’. Urban Studies, 52(10), 1774–1790.

    Article  Google Scholar 

  • Lu, C., Qi, W., Li, H., Sun, Y., Qin, T. T., & Wang, N. N. (2012). Application of 2D and 3D landscape pattern indices in landscape pattern analysis of mountainous area at county level. Chinese Journal of Applied Ecology, 23(5), 1352–1358.

    Google Scholar 

  • Markazi-Moghaddam, N., Arab, M., Ravaghi, H., Rashidian, A., Khatibi, T., & Zargar Balaye Jame, S. (2016). A knowledge map for hospital performance concept: Extraction and analysis—a narrative review article. Iranian Journal of Public Health, 45(7), 843–854.

    Google Scholar 

  • McGranahan, G., Balk, D., & Anderson, B. (2007). The rising tide: Assessing the risks of climate change and human settlements in low elevation coastal zones. Environment and Urbanization, 19(1), 17–37.

    Article  Google Scholar 

  • Meng, D., Yang, S., Gong, H., Li, X., & Zhang, J. (2016). Assessment of thermal environment landscape over five megacities in China based on Landsat 8. Journal of Applied Remote Sensing, 10(2), 026034.

    Article  Google Scholar 

  • Michael, S. V., & Rutherford, G. (2014). Keywords in the mental lexicon. Journal of Memory and Language, 73, 131–147.

    Article  Google Scholar 

  • Newman, M. E., & Watts, D. J. (1999). Renormalization group analysis of the small-world network model. Physics Letters A, 263(4), 341–346.

    MathSciNet  Article  MATH  Google Scholar 

  • Ravallion, M., Chen, S., & Sangraula, P. (2007). New evidence on the urbanization of global poverty. Population and Development Review, 33(4), 667–701.

    Article  Google Scholar 

  • Ronda-Pupo, G. A., & Guerras-Martin, L. A. (2012). Dynamics of the evolution of the strategy concept 1962–2008: A co-word analysis. Strategic Management Journal, 33(2), 162–188.

    Article  Google Scholar 

  • Su, H. N., & Lee, P. C. (2010). Mapping knowledge structure by keyword co-occurrence: A first look at journal papers in technology foresight. Scientometrics, 85(1), 65–79.

    Article  Google Scholar 

  • Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of small-world networks. Nature, 393(6684), 440–442.

    Article  Google Scholar 

  • Wu, W., Xu, L. P., Zhang, M., Ou, M. H., & Fu, H. Y. (2016). Impact of landscape metrics on grain size effect in different types of patches: A case study of Wuxi City. Shengtai Xuebao/Acta Ecologica Sinica, 36(9), 2740–2749.

    Google Scholar 

  • Wu, K. Y., Ye, X. Y., Qi, Z. F., et al. (2013a). Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China. Cities, 31, 276–284.

    Article  Google Scholar 

  • Wu, W., Zhou, S., Wei, Y., & Chang, T. (2013b). Modeling spatial determinants of land urbanization in urban fringe. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 29(16), 220–228.

    Google Scholar 

  • Yeoman, F., & Mac Nally, R. (2005). The avifaunas of some fragmented, periurban, coastal woodlands in south-eastern Australia. Landscape and Urban Planning, 72(4), 297–312.

    Article  Google Scholar 

  • Zhang, Q. T., Sun, X. M., Li, F., et al. (2013). The research hotspots analysis of cerebral hemorrhage treatment by PubMed. BioTechnology An Indian Journal, 8(3), 363–366.

    Google Scholar 

  • Zhang, W., Zhang, Q., Yu, B., & Zhao, L. (2015). Knowledge map of creativity research based on keywords network and co-word analysis, 1992–2011. Quality & Quantity, 49(3), 1023–1038.

    Article  Google Scholar 

  • Zhao, J. J., & Chai, L. H. (2015a). A novel approach for urbanization level evaluation based on information entropy principle: A case of Beijing. Physica A, 430, 114–125.

    Article  Google Scholar 

  • Zhao, S., & Chai, L. H. (2015b). A new assessment approach for urban ecosystem health basing on maximum information entropy method. Stochastic Environmental Research and Risk Assessment, 29(6), 1601–1613.

    Article  Google Scholar 

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Correspondence to Qian-Ru Zhang.

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Qian-Ru Zhang, Yue Li, Jia-Shu Liu, Yi-Dan Chen and Li-He Chai contributed equally to this study.

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Zhang, QR., Li, Y., Liu, JS. et al. A dynamic co-word network-related approach on the evolution of China’s urbanization research. Scientometrics 111, 1623–1642 (2017). https://doi.org/10.1007/s11192-017-2314-1

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  • DOI: https://doi.org/10.1007/s11192-017-2314-1

Keywords

  • Knowledge system (KS)
  • Co-word network
  • China’s urbanization research (CUR)
  • Scale-free network
  • Small-world network