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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 forwa...

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Detalles Bibliográficos
Autores principales: Liu, Na, Shapira, Philip, Yue, Xiaoxu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550099/
https://www.ncbi.nlm.nih.gov/pubmed/34720254
http://dx.doi.org/10.1007/s11192-021-03868-4
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author Liu, Na
Shapira, Philip
Yue, Xiaoxu
author_facet Liu, Na
Shapira, Philip
Yue, Xiaoxu
author_sort Liu, Na
collection PubMed
description 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.
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spelling pubmed-85500992021-10-29 Tracking developments in artificial intelligence research: constructing and applying a new search strategy Liu, Na Shapira, Philip Yue, Xiaoxu Scientometrics Article 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. Springer International Publishing 2021-02-25 2021 /pmc/articles/PMC8550099/ /pubmed/34720254 http://dx.doi.org/10.1007/s11192-021-03868-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Liu, Na
Shapira, Philip
Yue, Xiaoxu
Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title_full Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title_fullStr Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title_full_unstemmed Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title_short Tracking developments in artificial intelligence research: constructing and applying a new search strategy
title_sort tracking developments in artificial intelligence research: constructing and applying a new search strategy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8550099/
https://www.ncbi.nlm.nih.gov/pubmed/34720254
http://dx.doi.org/10.1007/s11192-021-03868-4
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