Bibliometric analysis of natural language processing using CiteSpace and VOSviewer

Abstract

Natural Language Processing (NLP) holds a pivotal position in the domains of computer science and artificial intelligence (AI). Its focus is on exploring and developing theories and methodologies that facilitate seamless and effective communication between humans and computers through the use of natural language. First of all, In this paper, we employ the bibliometric analysis tools, namely CiteSpace and VOSviewer (Visualization of Similarities viewer) are used as the bibliometric analysis software in this paper to summarize the domain of NLP research and gain insights into its core research priorities. What is more, the Web of Science(WoS) Core Collection database serves as the primary source for data acquisition in this study. The data includes 4803 articles on NLP published from 2011 to May 15, 2024. The trends and types of articles reveal the developmental trajectory and current hotspots in NLP. Finally, the analysis covers eight aspects: volume of published articles, classification, countries, institutional collaboration, author collaboration network, cited author network, co-cited journals, and co-cited references. The applications of NLP are vast, spanning areas such as AI, electronic health records, risk, task analysis, data mining, computational modeling. The findings suggest that the emphasis of future research ought to focus on areas like AI, risk, task analysis, and computational modeling. This paper provides learners and practitioners with a comprehensive insight into the current status and emerging trends in NLP.