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Comparing the topological rank of journals in Web of Science and Mendeley

Heliyon. 2019. Vol. 5. No. 7. P. e02089-1–e02089-9.
Katchanov Y. L., Markova Y., Shmatko N.

Recently, there has been a surge of interest in new data emerged due to the rapid development of the information technologies in scholarly communication. Since the 2010s, altmetrics has become a common trend in scientometric research. However, researchers have not treated in much detail the question of the probability distributions underlying these new data. The principal objective of this study was to investigate one of the classic problems of scientometrics—the problem of citation and readership distributions. The study is based on the data obtained from two information systems: Web of Science and Mendeley. Here we based on the concept of the cumulative empirical distribution function to explore the differences and similarities between citations and readership counts of biological journals indexed in Web of Science and Mendeley. The basic idea was to determine, for any journal, a “size” (it is said to be the topological rank) of citation and readership empirical cumulative distributions, and then to compare distributions of the topological ranks of Web of Science and Mendeley. In order to verify our model, we employ it to the bibliometric and altmetric research of 305biological journals indexed in Journal Citation Reports 2015. The findings show that both distributions of the topological rank of biological journals are statistically close to the Wakeby distribution. The findings presented in this study add to our understanding of information processes of the scholarly communication in the new digital environment.

Research target: Social Sciences Mathematics
Priority areas: sociology IT and mathematics
Language: English
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Keywords: Bibliometricsinformation technologies (IT)AltmetricsBiological journals
Publication based on the results of:
Monitoring behavior of innovation actors: innovation activity of knowledge-intensive business services firms; innovation patterns of highly qualified R&D personnel (2019)
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