Science behind AI: the evolution of trend, mobility, and collaboration
Sha Yuan,
Zhou Shao,
Xingxing Wei,
Jie Tang (),
Wendy Hall,
Yongli Wang,
Ying Wang and
Ye Wang
Additional contact information
Sha Yuan: Tsinghua University
Zhou Shao: Tsinghua University
Xingxing Wei: Beihang University
Jie Tang: Tsinghua University
Wendy Hall: University of Southampton
Yongli Wang: Nanjing University of Science and Technology
Ying Wang: The Ministry of Science and Technology of China
Ye Wang: The Ministry of Science and Technology of China
Scientometrics, 2020, vol. 124, issue 2, No 9, 993-1013
Abstract:
Abstract In this era of interdisciplinary science, many scientific achievements, such as artificial intelligence (AI), have brought dramatic revolutions to human society. The increasing availability of digital data on scholarly outputs offers unprecedented opportunities to explore science of science (SciSci). Despite many significant works have been done on SciSci, substantial disciplinary differences in different domains make some insights inadequate within particular fields. One thing standing out is that knowledge concerning the science behind AI is sorely lacking. In this work, we study the evolution of AI from three dimensions, including the evolution of trend, mobility, and collaboration. We find that the AI research hotspots have shifted from theory to application. The USA, which has the largest number of distinguished AI scientists, appeals most to the global AI talents. The brain drain problem of AI scientists is increasingly serious in developing countries. The ties among the AI elites are highly clustered in the collaboration network. Overall, our work aims to serve as a starter and support the development of AI exploring in a visionary way. The related demos are available online in AMiner ( https://www.aminer.cn/ai10 , https://trend.aminer.org ).
Keywords: Artificial intelligence; Science of science; Trend; Career trajectory; Collaboration (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (8)
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DOI: 10.1007/s11192-020-03423-7
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