International Cooperation Among Artificial Intelligence Research Teams Based on Regional Cooperation Models

Abstract

The paper explores the regional cooperation model and the differences among artificial intelligence research teams. It is helpful to reveal the status and strategies of scientific cooperation models across regions or within regions. We identified the world of artificial intelligence research teams with co-authorship network, and then identified the leading team based on the Number of Publications, Number of Citations, H-index, Weighted Degree Centrality, Betweenness Centrality, and Closeness Centrality. Based on the identified artificial intelligence research leading teams, this paper divides different types of cooperation models by region and comprehensively analyzed the three aspects of geographical distribution, cooperation indicators, and cooperation topics in the research teams from the perspective of comparisons. In order to find the international gap between China and other countries, we still highlight the difference between China's participation and non-participation in cooperation. The research results show that Chinese and their foreign research maintain close ties with major scientific research countries; international cooperation is widespread and is conducive to crossing into the leading team; China's domestic cooperation is higher than in other countries, and their domestic cooperation research is mainly manifested in the data processing and application level, while the core technology and basic algorithm levels need to cooperate with foreign countries.