Artificial intelligence theory: a bibliometric analysis

E. Romero-Riaño, D. Rico-Bautista, M. Martinez-Toro, Y. Medina-Cárdenas, N. Rico-Bautista

Research output: Articles / NotesConference articlepeer-review

6 Scopus citations

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.

Original languageEnglish
Article number012078
JournalJournal of Physics: Conference Series
Volume2046
Issue number1
DOIs
StatePublished - 18 Oct 2021
Event5+1 International Meeting for Researchers in Materials and Plasma Technology, 5+1 IMRMPT 2021 - Medellin, Colombia
Duration: 2 Jun 20214 Jun 2021

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