ANALYSIS OF POSSIBILITIES OF ARTIFICIAL INTELLIGENCE APPLICATION IN MODERN SCIENTOMETRY AND BIBLIOMETRY

The purpose of the research work is to identify and analyze the possibilities of the artificial intelligence application in scientometry and bibliometry. Artificial intelligence is considered in the work as a section of informatics. A special feature of the article is its interdisciplinary character. The research methods include: specification of research boundaries, theoretical analysis, synthesis, comparison of entities, systematization of the material, interpretation and generalization of results. To characterize the field of the artificial intelligence application, the general features of modern scientometry and bibliometry are presented and analyzed, their specific features are highlighted, the definition for each of the two metric disciplines is worked out taking into account their differences; their tasks and needs are considered. The main content of artificial intelligence technology is revealed, its basic definitions are presented, spheres of its possible application in scientometry and bibliometry are analyzed, including the common directions of its usage for the two disciplines. The main spheres of application were identified along with using the results of current research by Russian, Indian, Iranian, Chinese, Western scientists, as well as researchers from SouthEast Asia. It is concluded that artificial intelligence nowadays is becoming increasingly widespread; its tools and methods contribute to optimizing the solution of scientometric and bibliometric tasks, providing an increase in the speed and quality of processing, analysis and presentation of scientific information and data, including the modern category of big data.

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Publication Details

Journal
RSUH/RGGU Bulletin Series Information Science Information Security Mathematics
Published
2025-01-01
DOI
https://doi.org/10.28995/2686-679x-2025-2-19-40
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
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article

ANALYSIS OF POSSIBILITIES OF ARTIFICIAL INTELLIGENCE APPLICATION IN MODERN SCIENTOMETRY AND BIBLIOMETRY

Elena V. Melnikova, Valentina A. Tsvetkova
RSUH/RGGU Bulletin Series Information Science Information Security Mathematics
Engineering Education and Technology
article

ANALYSIS OF POSSIBILITIES OF ARTIFICIAL INTELLIGENCE APPLICATION IN MODERN SCIENTOMETRY AND BIBLIOMETRY

Elena V. Melnikova, Valentina A. Tsvetkova
article en

Abstract

The purpose of the research work is to identify and analyze the possibilities of the artificial intelligence application in scientometry and bibliometry. Artificial intelligence is considered in the work as a section of informatics. A special feature of the article is its interdisciplinary character. The research methods include: specification of research boundaries, theoretical analysis, synthesis, comparison of entities, systematization of the material, interpretation and generalization of results. To characterize the field of the artificial intelligence application, the general features of modern scientometry and bibliometry are presented and analyzed, their specific features are highlighted, the definition for each of the two metric disciplines is worked out taking into account their differences; their tasks and needs are considered. The main content of artificial intelligence technology is revealed, its basic definitions are presented, spheres of its possible application in scientometry and bibliometry are analyzed, including the common directions of its usage for the two disciplines. The main spheres of application were identified along with using the results of current research by Russian, Indian, Iranian, Chinese, Western scientists, as well as researchers from SouthEast Asia. It is concluded that artificial intelligence nowadays is becoming increasingly widespread; its tools and methods contribute to optimizing the solution of scientometric and bibliometric tasks, providing an increase in the speed and quality of processing, analysis and presentation of scientific information and data, including the modern category of big data.

RSUH/RGGU Bulletin Series Information Science Information Security Mathematics(2)
Openalex Percentile: Top 70%
Engineering Education and Technology
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