Exploring the Major Trends and Emerging Themes of Artificial Intelligence in the Scientific Leading Journals amidst the COVID-19 Era

Abstract

Artificial intelligence (AI) has recently become the focus of academia and practitioners, reflecting the substantial evolution of scientific production in this area, particularly during the COVID-19 era. However, there is no known academic work exploring the major trends and the extant and emerging themes of scientific research production of AI leading journals. To this end, this study is to specify the research progress on AI among the top-tier journals by highlighting the development of its trends, topics, and key themes. This article employs an integrated bibliometric analysis using evaluative and relational metrics to analyze, map, and outline the key trends and themes of articles published in the leading AI academic journals, based on the latest CiteScore of Scopus-indexed journals between 2020 and 2021. The findings depict the major trends, conceptual and social structures, and key themes of AI leading journals’ publications during the given period. This paper represents valuable implications for concerned scholars, research centers, higher education institutions, and various organizations within different domains. Limitations and directions for further research are outlined.

Exploring the Scholarly Landscape: AI Teaching and Learning in Adult Education

“…Notable examples include the scoping literature review conducted by Laupichler et al (2022) on AI literacy in higher and adult education, the comprehensive AI policy education framework developed by Chan (2023) for university teaching and learning, and the systematic review conducted by Kizilcec (2023) on research pertaining to AI applications in higher education. Furthermore, the table serves to emphasize the incorporation of various types of scholarly communication, including reviews, books, and editorials, thereby underscoring the multidimensional character of scholarly discourse within this field (Hussain & Ahmad, 2023;Soliman et al, 2023;Bawack et al, 2022;Liu et al, 2022;McGillivray et al, 2022). This research also found the dataset analysis of 435 articles pertaining to the teaching and learning of AI for adult learners, offers a thorough examination of the dispersion of these publications throughout several source categories (refer to Table 2).…”

“…The aforementioned scholarly references collectively provide a comprehensive understanding of the various aspects of academic involvement in AI-driven adult pedagogy. This involvement is demonstrated through participation in conferences, publication of research findings, and utilization of diverse platforms (Hussain & Ahmad, 2023;Holmes et al, 2022;Seo et al, 2021;Ahmad et al, 2020;Soliman et al, 2023;Guo et al, 2020).…”

Open Datasets in Human Activity Recognition Research—Issues and Challenges: A Review

“…There has been a rise in the use of network analysis as a method for exploring the interconnections between various concepts and phrases in the academic literature [81]. Unit analysis as a keyword and type analysis as co-occurrence allow researchers to find important phrases that are regularly linked with the unit of study, allowing them to begin to construct a more comprehensive knowledge of the issue at hand [82].…”

Fostering social media user intentions: AI-enabled privacy and intrusiveness concerns

“…Artificial intelligence (AI) is currently essential as businesses move towards a more algorithmic environment (Soliman et al, 2023). Technology is becoming a participant in SJME the value exchange process rather than just a tool used by stakeholders (Aguirre et al, 2023).…”