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September 19, 2023 10:30, XXV Conference "Scientific service in Internet — 2023", 19-21 September 2023, online


Using the journal citation graph to analyze the RSCI thematic rating

E. A. Znamenskayaa, A. A. Pechnikovb, D. Chebukova

a Steklov Mathematical Institute of Russian Academy of Sciences, Moscow
b Institute of Applied Mathematical Research of the Karelian Research Centre RAS, Petrozavodsk

Abstract: t. The problem of import substitution in the spring of 2022 affected many areas of activity in Russia, including assessments of the effectiveness of scientific activities. A national system for evaluating the effectiveness of scientific research and development is being created using the database of leading Russian journals Russian Science Citation Index (RSCI). The article presents some results of the analysis of the RSCI normalized rating published in December 2022. The work was performed using the journal citation graph constructed from the data Math-Net.Ru. Using the example of thematic group OECD 101.Mathematics shows that in the presence of a large number of self-citations of journals, a relationship is found between the normalized rating and the number of references, and the relationship with self-citation is somewhat stronger than without self-citation. Analysis of the distribution of journals by thematic groups shows that using a single attribute, such as the OECD, as a criterion does not allow forming a group as a community of journals with a single strongly connected component in the citation graph. It is concluded that the research methods of journal citation graphs are a good basis for a comparative analysis of the characteristics of journals and their ranking, which means they can be used as tools for further development and improvement of journal ratings.

Keywords: rating of journals, Russian Science Citation Index, Math-Net.Ru, journal citation graph, impact factor, eigenvector centrality.

Website: https://keldysh.ru/abrau/2023/theses/16.pdf


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