A method for assessing the productivity trends of collective scientific subjects based on the modified PageRank algorithm

Authors

DOI:

https://doi.org/10.15587/1729-4061.2023.273929

Keywords:

PageRank algorithm, scientific work, collective scientific subject, scientometrics, scientific productivity

Abstract

The task of calculating the productivity of collective scientific subjects is a relevant issue in scientometrics. This study formalized the problem of assessing productivity trends of collective scientific subjects. The TWPR-CI method for calculating the performance based on the modified PageRank algorithm is described. Formulas for calculating productivity have been derived that make it possible to take into account a change in the productivity of collective scientific subjects over time. The indicators of the basic average absolute change in performance and the chain average relative change in performance were chosen as the basis. To select promising, from the point of view of scientific work, collective subjects, preference is given to those whose basic average absolute change in productivity is positive or the chain average relative change in productivity exceeds unity. Verification of the method for assessing performance trends of collective scientific entities based on the modified PageRank algorithm using the public dataset Citation Network Dataset was carried out. The dataset includes more than 5 million scientific publications and 48 million citations. The citation of scientific publications of 27,500 collective scientific subjects for the period from 2000 to 2022 was analyzed. For this period, for 15 selected collective scientific subjects, performance is calculated using the TWPR-CI method, as well as estimates of productivity trends based on their average relative change. There are three classes of collective scientific subjects according to productivity trends. The results indicate the relevance of the proposed method for quantifying the productivity trends of collective scientific entities (higher education institutions, scientific institutes, laboratories, and other institutions engaged in scientific activities)

Author Biographies

Yurii Andrashko, Uzhhorod National University

PhD, Associate Professor

Department of System Analysis and Optimization Theory

Oleksandr Kuchanskyi, Taras Shevchenko National University of Kyiv

Doctor of Technical Sciences, Head of Department

Department of Information Systems and Technology

Andrii Biloshchytskyi, Astana IT University; Kyiv National University of Construction and Architecture

Doctor of Technical Sciences, Professor, Vice-Rector for Science and Innovation

Department of Information Technologies

Oleksandr Pohoriliak, Uzhhorod National University

PhD

Department of Probability Theory and Mathematical Analysis

Myroslava Gladka, Taras Shevchenko National University of Kyiv

PhD, Associate Professor

Department of Information Systems and Technology

Ganna Slyvka-Tylyshchak, Uzhhorod National University

Doctor of Physical and Mathematical Sciences, Head of Department

Department of Probability Theory and Mathematical Analysis

Dmytro Khlaponin, Kyiv National University of Construction and Architecture

PhD, Associate Professor

Department of Political Sciences and Law

Ivan Chychkan, Taras Shevchenko National University of Kyiv

PhD, Associate Professor

Department of Information Systems and Technology

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A method for assessing the productivity trends of collective scientific subjects based on the modified PageRank algorithm

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Published

2023-02-28

How to Cite

Andrashko, Y., Kuchanskyi, O., Biloshchytskyi, A., Pohoriliak, O., Gladka, M., Slyvka-Tylyshchak, G., Khlaponin, D., & Chychkan, I. (2023). A method for assessing the productivity trends of collective scientific subjects based on the modified PageRank algorithm. Eastern-European Journal of Enterprise Technologies, 1(4 (121), 41–47. https://doi.org/10.15587/1729-4061.2023.273929

Issue

Vol. 1 No. 4 (121) (2023): Mathematics and Cybernetics - applied aspects

Section

Mathematics and Cybernetics - applied aspects

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Copyright (c) 2023 Yurii Andrashko, Oleksandr Kuchanskyi, Andrii Biloshchytskyi, Oleksandr Pohoriliak, Myroslava Gladka, Ganna Slyvka-Tylyshchak, Dmytro Khlaponin, Ivan Chychkan

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