Tracking developments in artificial intelligence research: constructing and applying a new search strategy

Artificial intelligence, as an emerging and multidisciplinary domain of research and innovation, has attracted growing attention in recent years. Delineating the domain composition
of artificial intelligence is central to profiling and tracking its development and trajectories. This paper puts forward a bibliometric definition for artificial intelligence which can
be readily applied, including by researchers, managers, and policy analysts. Our approach starts with benchmark records of artificial intelligence captured by using a core keyword
and specialized journal search. We then extract candidate terms from high frequency keywords of benchmark records, refine keywords and complement with the subject category
“artificial intelligence”. We assess our search approach by comparing it with other three recent search strategies of artificial intelligence, using a common source of articles from
the Web of Science. Using this source, we then profile patterns of growth and international diffusion of scientific research in artificial intelligence in recent years, identify top
research sponsors in funding artificial intelligence and demonstrate how diverse disciplines contribute to the multidisciplinary development of artificial intelligence. We conclude with
implications for search strategy development and suggestions of lines for further research. 

• Philip Shapira

Liu, N., Shapira, P. & Yue, X. Tracking developments in artificial intelligence research: constructing and applying a new search strategy. Scientometrics 126, 3153–3192 (2021). https://doi.org/10.1007/s11192-021-03868-4

• Science, Technology, and Innovation Policy

• Jimmy and Rosalynn Carter School of Public Policy