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Complex network properties of Chinese natural science basic research

Author

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  • Liu, Jianguo
  • Dang, Yanzhong
  • Wang, Zhongtuo

Abstract

In this paper, we studied the research areas of Chinese natural science basic research from a point view of complex network. Two research areas are considered to be connected if they appear in one fund proposal. The explicit network of such connections using data from 1999 to 2004 is constructed. The analysis of the real data shows that the degree distribution of the research areas network (RAN) may be better fitted by the exponential distribution. It displays small world effect in which randomly chosen pairs of research areas are typically separated by only a short path of intermediate research areas. The average distance of RAN decreases with time, while the average clustering coefficient increases with time, which indicates that the scientific study would like to be integrated together in terms of the studied areas. The relationship between the clustering coefficient C(k) and the degree k indicates that there is no hierarchical organization in RAN.

Suggested Citation

  • Liu, Jianguo & Dang, Yanzhong & Wang, Zhongtuo, 2006. "Complex network properties of Chinese natural science basic research," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 578-586.
    • Handle: RePEc:eee:phsmap:v:366:y:2006:i:c:p:578-586
    DOI: 10.1016/j.physa.2005.10.036
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    Citations

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    Cited by:

    1. Yang, Guang-Yong & Hu, Zhao-Long & Liu, Jian-Guo, 2015. "Knowledge diffusion in the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 429-436.
    2. Shizhong Ai & Rong Du & Cathal M. Brugha & Hongpeng Wang, 2016. "Pointing to Priorities for Multiple Criteria Decision Making — The Case of a MIS-Based Project in China," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(03), pages 683-702, May.
    3. Wang, Jiang-Pan & Guo, Qiang & Yang, Guang-Yong & Liu, Jian-Guo, 2015. "Improved knowledge diffusion model based on the collaboration hypernetwork," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 250-256.
    4. Liu, Ji & Deng, Guishi, 2009. "Link prediction in a user–object network based on time-weighted resource allocation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(17), pages 3643-3650.
    5. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.

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