Complex networks properties of Chinese natural science basic research

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 bf 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.