A brief network analysis of Artificial Intelligence publication
This provides a descriptive overview of AI publication trends for researchers and policymakers, but is incremental as it applies existing network analysis methods to AI publication data.
The authors analyzed the history of AI research through a statistical study of publications since 1940 using IEEE data, revealing that leading communities are in the USA, China, Europe, and Japan, with strong interactions between fields like Data Mining and Computer Vision.
In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between different institutes are showed. The result shows that the leading community of AI research are mainly in the USA, China, the Europe and Japan. The key institutes, authors and the research hotspots are revealed. It is found that the research institutes in the fields like Data Mining, Computer Vision, Pattern Recognition and some other fields of Machine Learning are quite consistent, implying a strong interaction between the community of each field. It is also showed that the research of Electronic Engineering and Industrial or Commercial applications are very active in California. Japan is also publishing a lot of papers in robotics. Due to the limitation of data source, the result might be overly influenced by the number of published articles, which is to our best improved by applying network keynode analysis on the research community instead of merely count the number of publish.