A Ten-year Review and Visual Analysis of Global Artificial Intelligence Research—A Bibliometric Analysis in CiteSpace Based on Highly Cited Literature

Abstract

Taking the highly cited literature related to artificial intelligence over the ten-year span between 2009 and 2019 from the Web of Science database as the data sample, this paper has analyzed the distribution of literature, hot topics of research, frontier research and evolution of artificial intelligence by using CiteSpace and applying dual-map overlay, co-word and co-citation analysis, among other bibliometric approaches. The research findings indicate full-fledged multidisciplinary features of artificial intelligence, but interdisciplinary integration is still at a nascent stage; most of the existing researches are focused on fundamental technologies, while applications are quite limited, with more applications of the computer vision technologies; deep learning is garnering the most interest, while a cutting-edge research theme could be the combination of quantum physics and machine learning.

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