Application of Time-Weighted PageRank Method with Citation Intensity for Assessing the Recent Publication Productivity and Partners Selection in R&D Collaboration

Andrii Biloshchytskyi, Oleksandr Kuchanskyi (), Aidos Mukhatayev, Yurii Andrashko, Sapar Toxanov, Adil Faizullin and Khanat Kassenov
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Andrii Biloshchytskyi: University Administration Office, Astana IT University, Astana 010000, Kazakhstan
Oleksandr Kuchanskyi: Department of Computational and Data Science, Astana IT University, Astana 010000, Kazakhstan
Aidos Mukhatayev: Department of Social Disciplines, Astana IT University, Astana 010000, Kazakhstan
Yurii Andrashko: Department of System Analysis and Optimization Theory, Uzhhorod National University, 88000 Uzhhorod, Ukraine
Sapar Toxanov: Center of Competence and Excellence, Astana IT University, Astana 010000, Kazakhstan
Adil Faizullin: University Administration Office, Astana IT University, Astana 010000, Kazakhstan
Khanat Kassenov: Quality Assurance Department, Astana IT University, Astana 010000, Kazakhstan

Publications, 2024, vol. 12, issue 4, 1-21

Abstract: This article considers the problem of assessing the recent publication productivity of scientists based on PageRank class methods and proposes to use these assessments to solve the problem of selecting scientific partners for R&D projects. The methods of PageRank, Time-Weighted PageRank, and the Time-Weighted PageRank method with Citation Intensity (TWPR-CI) were used as a basis for calculating the publication productivity of individual subjects or scientists. For verification, we used the Citation Network Dataset (Ver. 14) of more than 5 million STEM publications with 36 million citations. The dataset is based on data from ACM, DBLP, and Microsoft Academic Graph databases. Only those individual subjects who published at least two articles after 2000, with at least one of these articles cited at least once before 2023 year, were analyzed. Thus, the number of individual subjects was reduced to 1,042,122, and the number of scientific publications was reduced to 2,422,326. For each of the methods, a range of estimates of productivity is indicated, which are obtained as a result and possible options for making decisions on the selection of potential individual subjects as performers of R&D projects. One of the key advantages of the TWPR-CI method is that it gives priority to those researchers who have recently published and been cited frequently in their respective research areas. This ensures that the best potential R&D project executors are selected, which should minimize the impact of subjective factors on this choice. We believe that the proposed concept for selecting potential R&D project partners could help to reduce the risks associated with these projects and facilitate the involvement of the most suitable specialists in the relevant area of knowledge.

Keywords: Time-Weighted PageRank; scientific research; individual subjects; citation intensity; publication productivity; partner selection process; R&D; scholarly communication (search for similar items in EconPapers)
JEL-codes: A2 D83 L82 (search for similar items in EconPapers)
Date: 2024
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