Priority Areas of Scientific Cooperation between Scientists of Russia, Iran, India, and Turkey: Bibliometric Analysis According to the InCites Database (2011–2021)

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-11-24 DOI:10.3103/S0005105523050047
V. A. Markusova, A. N. Libkind, A. V. Zolotova, N. A. Kotelnikova
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Abstract

We conducted an investigation into the patterns of international collaboration among publications by Russian scholars, specifically articles and reviews, with their counterparts from Iran, India, and Turkey during the period spanning from 2011 to 2021. The selection of these countries was based on their growing role on the world science stage and increased partnership with Russia over the last ten years. The primary objectives of this study are to conduct a comprehensive analysis investigating the patterns of Russian collaborations with selected countries. This includes revealing the disciplinary priorities in their international collaborations, identifying the top organizations involved, and understanding the model of co-authorship. The findings indicate a growing partnership across various disciplines, with a particular focus on basic research in physics and clinical medicine. The top collaborating organizations in Russia, as well as in each of the studied countries (Iran, India, and Turkey), are either wholly or partially funded by their respective national governments. Furthermore, the values of bibliometric indicators for these collaborative publications indicate a high level of quality. Our findings could benefit decision-makers by providing evidence-based data and funding agencies.

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俄罗斯、伊朗、印度和土耳其科学家科学合作的优先领域:基于InCites数据库的文献计量分析(2011-2021)
我们对2011年至2021年期间俄罗斯学者与伊朗、印度和土耳其学者发表的出版物(特别是文章和评论)之间的国际合作模式进行了调查。这些国家的选择是基于它们在世界科学舞台上日益增长的作用以及在过去十年中与俄罗斯加强的伙伴关系。本研究的主要目的是进行全面分析,调查俄罗斯与选定国家的合作模式。这包括揭示他们在国际合作中的学科优先级,确定参与的顶级组织,以及理解合作模式。研究结果表明,各个学科之间的合作关系日益密切,特别是物理学和临床医学的基础研究。俄罗斯以及被研究的每个国家(伊朗、印度和土耳其)的顶级合作组织全部或部分由各自的国家政府资助。此外,这些合作出版物的文献计量指标值表明质量很高。我们的发现可以通过提供基于证据的数据和资助机构使决策者受益。
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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
期刊介绍: Automatic Documentation and Mathematical Linguistics  is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.
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