Artificial intelligence theory: a bibliometric analysis

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Abstract

This article analyzes the evolution of artificial intelligence research from the bibliometric perspective. Bibliometrics, as one sub-field of scientometric, is defined as the use of statistical methods for analyzing publication data. A total of 8334 papers were identified divided into two periods, 2010-2014 and 2015-2019. To recognize the trends of artificial intelligence research, bibliometric analysis and social network analysis are combined to judge the current situation and development trends. The results revealed the keywords with the highest occurrence and those with the strongest linkage strength from cluster analysis. Moreover, the study of artificial intelligence was found to be an active field of growth, and the words that control the knowledge area were identified. The results of this study will facilitate the understanding of the progress and trends in artificial intelligence for researchers interested in understanding its evolution.

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Romero-Riaño, E., Rico-Bautista, D., Martinez-Toro, M., Medina-Cárdenas, Y., & Rico-Bautista, N. (2021). Artificial intelligence theory: a bibliometric analysis. In Journal of Physics: Conference Series (Vol. 2046). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/2046/1/012078

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