Generative AI Research Landscape: A Bibliometric Analysis from Scopus Database

We provide here a comprehensive bibliometric study of the research environment in the field of Generative AI (Artificial Intelligence), as recognized by articles that have been indexed in the Scopus database up to this point. For the purpose of author profiling, keyword co-occurrence and visualization (map of science), bibliographic coupling, citations, and cocitations, this study makes use of VOSviewer. This helps to uncover important contributions to computational fluid dynamics (CFD) while also permitting a fine-grained portrayal of developing patterns. The findings indicate 12 prolific authors, 33 core keywords, and other publications that have received the most citations. In addition, the study provides a list of thirty of the most prominent publishing sites as well as seventeen references that have received a large number of citations. These references are representative of the collaborative and multidisciplinary features of research on generative artificial intelligence. The findings of this study offer academics, practitioners, and policymakers with valuable information that may be used to influence future research paths in generative artificial intelligence and to build new policies.

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Published
2024-09-04
DOI
https://doi.org/10.1109/globalaisummit62156.2024.10947886
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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article

Generative AI Research Landscape: A Bibliometric Analysis from Scopus Database

Parul Dubey, Manjushree Nayak, A Ayineh Band, R. Ponmalar et al.
1 citations
Big Data and Business Intelligence
0.53
article

Generative AI Research Landscape: A Bibliometric Analysis from Scopus Database

Parul Dubey, Manjushree Nayak, A Ayineh Band, R. Ponmalar, Shraddha Raut, Anirudh Avinash Bhagwat
article en
1 citations

Abstract

We provide here a comprehensive bibliometric study of the research environment in the field of Generative AI (Artificial Intelligence), as recognized by articles that have been indexed in the Scopus database up to this point. For the purpose of author profiling, keyword co-occurrence and visualization (map of science), bibliographic coupling, citations, and cocitations, this study makes use of VOSviewer. This helps to uncover important contributions to computational fluid dynamics (CFD) while also permitting a fine-grained portrayal of developing patterns. The findings indicate 12 prolific authors, 33 core keywords, and other publications that have received the most citations. In addition, the study provides a list of thirty of the most prominent publishing sites as well as seventeen references that have received a large number of citations. These references are representative of the collaborative and multidisciplinary features of research on generative artificial intelligence. The findings of this study offer academics, practitioners, and policymakers with valuable information that may be used to influence future research paths in generative artificial intelligence and to build new policies.

Symbiosis International University (IN), National Institute of Science and Technology (IN), Raisoni Group of Institutions (IN)
Climate action
Openalex Percentile: Top 21%
Big Data and Business Intelligence
0.53
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Generative AI Research Landscape: A Bibliometric Analysis from Scopus Database — Parul Dubey, Manjushree Nayak, et al. · (2024) | TGRS Research Map | TGRS