Spatial and Temporal Evolution of the Chinese Artificial Intelligence Innovation Network

Abstract

Sustainable development has become a concern of all countries globally, and Artificial Intelligence technology emerges at this historic moment. However, few researchers have studied the innovation activities of the Artificial Intelligence industry from the macro-level. This paper focuses on the topological structure and the spatial pattern of the AI patent citation network in China over from 2000–2016. Our main research results are as follows: The network has experienced a striking growth in terms of the size and the number of linkages since 2000, but it has also developed unequally across regions. In the later stages, the network has formed a scale-free network that exhibits small-world property. The network nodes have shown an assortative trait property while weighted preferential attachment has not been significant. In addition, the high values of centrality and numerous linkages between nodes concentrate in the eastern part of China, especially in the Yangtze River Delta, Pearl River Delta, and Bohai Rim. Our results suggest that the AI innovation policies should expand the targets of technological exchange and cultivate more nodes as intermediaries of local knowledge transmission necessary to expand the network and develop the AI industry.