基于高被引华人科学家流动的城市网络空间演化分析

The geographical flow of talents is affecting innovation activities worldwide, so the research on the spatial structure evolution of talent flows is particularly important. This article uses the 2014-2015 global list of highly cited scientists as raw data to retrieve the study and work experience of scientists, uses cities as the research scale, and uses the P-space model to build a highly cited Chinese scientist flow network. At the same time, uses quantile regression analyzes the impact of whether scientists in core cities are more productive. We found that: (1) The city network of highly cited Chinese scientists has the characteristics of a small-world network, and the network space structure presents a "Y-shaped" structure. China-U. S., China-Europe, and China-Australia are the main sides. (2) This article analyzes the source cities and the target cities in which scientists move, and finds that Beijing, Cambridge(UStates), Shanghai are the city with a high degree. (3) The distribution of scientists shows a trend of spreading with the development of the stage. (4) Scientists in core cities have more high-quality paper output. The increase in the degree of centrality of scientists' target cities has a greater impact on the output of scientists.