Application of the friendship index and disparity filter for the analysis of bibliometric journal networks

Pechnikov A.A.
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The traditional approach to studying inter-journal communication involves analyzing journal citation graphs. This paper proposes a method for analyzing journal networks using a new type of bibliometric graph — a journal intersection graph based on the binary operation of set intersection — employing techniques grounded in the friendship index and the disparity function. The approach is demonstrated using a relatively small example of a real journal network, with data sourced from the All-Russian portal Math-Net.Ru information system: 63 journals from 2008–2021 meeting specific criteria, containing almost 69 thousand articles authored by 54 thousand individuals. The mathematical model of this real-world network is represented as an intersection graph using the Jaccard coefficient, which exhibits specific properties: low dimensionality, high graph density, and an edge weight distribution that is not approximated by a power law function. The obtained results include the network structure of connections within the studied set of journals, accounting for their degree of interaction, and the identification of significant vertices using the friendship index. This captures the graph’s structural properties, offers an obvious substantive interpretation, and allows for ranking journals by this metric. Thus, the method implements a tool for distinguishing between vertices that are leaders in terms of the friendship index and “network integrators” (based on closeness/betweenness centrality). It also demonstrates a qualitative change in structural properties when reducing graph density while maintaining connectivity, achieved by applying the disparity function. The sequential application of the disparity function while lowering the significance threshold allows for the identification of the graph’s core, containing the most strongly connected vertices. This, in turn, enables the determination of a set of vertices (and corresponding journals) that are simultaneously part of the core and have the highest significance according to the friendship index. An analysis of the levels of this resulting journal set within the “Belyi Spisok” (“White List”) shows these journals have a high rating. The findings provide a deeper understanding of the relationship structure within scientific journal networks and define new approaches for their study.

Keywords: network of scientific journals, bibliometric graph, intersection of sets, Jaccard coefficient, friendship index, disparity function
Citation in English: Pechnikov A.A. Application of the friendship index and disparity filter for the analysis of bibliometric journal networks // Computer Research and Modeling, 2026, vol. 18, no. 2, pp. 519-535
Citation in English: Pechnikov A.A. Application of the friendship index and disparity filter for the analysis of bibliometric journal networks // Computer Research and Modeling, 2026, vol. 18, no. 2, pp. 519-535
DOI: 10.20537/2076-7633-2026-18-2-519-535
URL: http://crm-en.ics.org.ru/journal/article/3721/
Creative Commons License This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

Copyright © 2026 Pechnikov A.A.

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