Mapping the Scientific Landscape of Artificial Intelligence in the Publications of Researchers from Tehran-based Universities: A Bibliometric Analysis of Scholarly Outputs Indexed in Scopus from 2015 to 2025

Document Type : Original Article

Authors

1 Master's degree, Faculty of Humanities, Tarbiat Modares University, Tehran, Iran

2 Master's degree, National Commission for UNESCO Library; Jundishapour Library (Iran Mall), Tehran, Iran

Abstract

Purpose: The aim of this study is to create a scientific map of the field of artificial intelligence based on the research output of scholars from Tehran universities, as recorded in the Scopus citation database.
Method: This research is applied in terms of its purpose and was conducted using a descriptive-analytical study method along with bibliometric techniques. Tools such as VOSviewer software were utilized to create scientific maps. In this study, we reviewed and analyzed scientific data related to artificial intelligence published by researchers from Tehran universities in the Scopus citation database. The data utilized comprised articles published in the field of artificial intelligence over a ten-year period, from 2015 to 2025.
Findings: Iranian researchers in the field of artificial intelligence are primarily engaged in machine learning, neural networks, and natural language processing. They have established significant international collaborations with researchers from various countries. Additionally, the majority of articles related to this field have been published by prominent and prestigious universities in Iran.
Conclusion: In recent years, there has been a significant increase in the production of scientific articles in the field of artificial intelligence at universities in Tehran, and this trend is expected to continue in the future. The findings of this study can assist policymakers and researchers in enhancing research strategies and fostering scientific collaborations in this domain.
 

Keywords

References

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Applied Scientometric Studies
Volume 1, Issue 3
October 2024
Pages 55-76

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