Global bibliometric mapping of the frontier of knowledge in the field of artificial intelligence for the period 1990–2019

Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramifications, in order to analyze its growth. The study was developed u...

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Bibliographic Details
Published in:The Artificial intelligence review 2023-02, Vol.56 (2), p.1699-1729
Main Authors: De la Vega Hernández, Iván Manuel, Urdaneta, Angel Serrano, Carayannis, Elias
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Artificial Intelligence
Bibliometrics
Computational linguistics
Computer Science
Data processing
Language processing
Natural language interfaces
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Summary:Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramifications, in order to analyze its growth. The study was developed under the bibliometric approach and considered the period 1990–2019. The steps followed were (i) Identification and selection of keyword terms in three methodological layers by a panel of experts. (ii) Design and application of an algorithm to identify these selected keywords in titles, abstracts, and keywords using terms in Web of Science to contrast them. (iii) Performing data processing based on the Journals of the Journal Citation Report during 2020. Knowing the evolution of a field of knowledge such as AI from a bibliometric study and subsequently establishing the ramifications of new research streams is in itself a relevant finding. Addressing a broad field of knowledge as AI from a multidisciplinary approach given the convergence it generates with other disciplines and specialties is of high strategic value for decision makers such as governments, academics, scientists, and entrepreneurs.
ISSN:0269-2821
1573-7462
DOI:10.1007/s10462-022-10206-4