Applied artificial intelligence : A bibliometric study of an International Journal

Abstract

Purpose: The study aims to conduct a bibliometric analysis of an international journal “Applied Artificial Intelligence (AAI)” to analyze publication trends, authorship patterns, collaborative networks, citation behaviors, and research hotspots of authors, organizations, and countries. Research Design/Methodology: “Applied Artificial Intelligence” is a peer-reviewed international journal, published by Taylor & Francis. The journal has published more than 1100 articles in 34 volumes so far. The idea was conceived to conduct the bibliometric study of the AAI journal. The data were collected from the Web of Science (WOS) database, owned by the Clarivate Analytics. A total of 1109 articles were retrieved and their metadata was collected for further analysis and interpretation. Additionally, the VOS viewer software was used for mapping and visualization of the bibliographic information. Findings: The journal has experienced positive growth in research productivity and negative growth in citations. Authors of 74 prominent countries have contributed to the journal and the USA has occupied the first position in publication count followed by Italy, India and England respectively. All the countries work in close collaboration and created a collaborative network and sub-networks. The USA is the pivot of the collaborative network, mostly collaborating with England, Japan, Italy, China and Germany. The keywords like the classification, optimization, algorithms and neural networks are the most common and hence the hot topics of research in the journal. Originality/Value: The main advantage of this study is that it provides profound knowledge of the content structure and developmental process of the journal to date. It is also valuable for researchers in the field of artificial intelligence to identify the research hotspots in this field.