A pilot model of the scientific journal network in Russia: An intersection graph analysis

Scientific journals play an important role as a key tool for advancing science and encouraging knowledge exchange during research collaboration. The relationships among them are extremely diverse and cluster together into a complex network of connections. Developing adequate mathematical models of such self-organizing systems is a serious problem that requires in-depth investigation. This article introduces an approach to analyze the journal network based on a new bibliographic graph in which the relationships among journals are defined by shared authorship, i.e., through the binary intersection of author sets. Two levels of journal interaction can be distinguished using consistent source data processing techniques and methods. At the lower level, the relationships among multiple journals are grouped by scientific topics. At the upper level, the interactions between these topics are established. The approach was validated through a pilot study of eLIBRARY.RU data. The findings demonstrate its feasibility and scalability potential.

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Publication Details

Journal
Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki
Published
2025-07-19
DOI
https://doi.org/10.26907/2541-7746.2025.2.311-328
Citations
1
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
1.32
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article

A pilot model of the scientific journal network in Russia: An intersection graph analysis

Andrey Anatolievich Pechnikov
1 citations
Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki
Complex Network Analysis Techniques
1.32
article

A pilot model of the scientific journal network in Russia: An intersection graph analysis

Andrey Anatolievich Pechnikov
article en
1 citations

Abstract

Scientific journals play an important role as a key tool for advancing science and encouraging knowledge exchange during research collaboration. The relationships among them are extremely diverse and cluster together into a complex network of connections. Developing adequate mathematical models of such self-organizing systems is a serious problem that requires in-depth investigation. This article introduces an approach to analyze the journal network based on a new bibliographic graph in which the relationships among journals are defined by shared authorship, i.e., through the binary intersection of author sets. Two levels of journal interaction can be distinguished using consistent source data processing techniques and methods. At the lower level, the relationships among multiple journals are grouped by scientific topics. At the upper level, the interactions between these topics are established. The approach was validated through a pilot study of eLIBRARY.RU data. The findings demonstrate its feasibility and scalability potential.

Učenye zapiski Kazanskogo gosudarstvennogo universiteta. Seriâ Fiziko-matematičeskie nauki/Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie naukiVol. 167(2)
Russian Academy of Sciences (RU), Karelian Research Centre (RU)
Openalex Percentile: Top 18%
Complex Network Analysis Techniques
1.32
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