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A Quantitative History of A.I. Research in the United States and China
arXiv - CS - Digital Libraries Pub Date : 2020-03-05 , DOI: arxiv-2003.02763 Daniel Ish, Andrew Lohn, Christian Curriden
arXiv - CS - Digital Libraries Pub Date : 2020-03-05 , DOI: arxiv-2003.02763 Daniel Ish, Andrew Lohn, Christian Curriden
Motivated by recent interest in the status and consequences of competition
between the U.S. and China in A.I. research, we analyze 60 years of abstract
data scraped from Scopus to explore and quantify trends in publications on A.I.
topics from institutions affiliated with each country. We find the total volume
of publications produced in both countries grows with a remarkable regularity
over tens of years. While China initially experienced faster growth in
publication volume than the U.S., growth slowed in China when it reached parity
with the U.S. and the growth rates of both countries are now similar. We also
see both countries undergo a seismic shift in topic choice around 1990, and
connect this to an explosion of interest in neural network methods. Finally, we
see evidence that between 2000 and 2010, China's topic choice tended to lag
that of the U.S. but that in recent decades the topic portfolios have come into
closer alignment.
更新日期：2020-06-12
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