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Classification of Bibliographic References to Determine the Mutual Influence of Large Areas of Knowledge

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Automatic Documentation and Mathematical Linguistics Aims and scope

Abstract

This paper discusses the structure of the list of the thematic categories of the Web of Science in connection with the incorrectness of calculations of the number of profiling publications contained in them, as well as a possible way out of the situation using bibliographic references. It is established that the comparison of citations between large sections of science confirms the strengthening of the mutual influence of the natural and social sciences and the humanities in interdisciplinarity of research.

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Notes

  1. It is also possible to form triples, quadruples, etc. of matched arrays, but such arrays are not considered in this paper.

  2. A more general definition of the concept of distribution of publications can be formulated as follows: a table, which indicates the number of publications corresponding to each item (thematic categories, journals, countries, years of publication, etc.) against it.

  3. The task of visual identification in an array exceeding 15 million references is almost unsolvable, and differences even in one sign in case of programmatic identification will lead to publications not being recognized as identical.

  4. An increase in the set of categories currently assigned to a journal in WoS automatically leads to an increase in the set of categories that characterize each of its publications.

  5. A more detailed list of indicators that allows one to get Method 1 used together with Method 2 is as follows: Array of source publications (SPs); Subarray of shared SPs; Share of the subarray of shared SPs: the ratio of the number of shared SPs to the total number of SPs (%); Array of nonunique (duplicate) references; Array of unique references; Subarray of nonunique (duplicate) shared references of the first kind; Share of the subarray of nonunique (duplicate) shared references of the first kind: the ratio of the number of nonunique shared references of the first kind to the total number of nonunique references (%); Subarray of unique shared references of the first kind; Share of the subarray of unique shared references of the first kind: the ratio of the number of unique shared references of the first kind to the total number of unique references (%); Joint subarray of nonunique (duplicate) shared references—the union of the set of shared references of the second kind with the set of shared references of the first kind (combined application of Methods 1 and 2); Share of the joint subarray of nonunique shared references: the ratio of the total number of nonunique (duplicate) shared references of the second kind, which is supplemented by nonunique shared references of the first kind, to the total number of nonunique references (combined application of Methods 1 and 2) (%); Joint subarray of unique shared references—union of the set of unique shared references of the second kind with the set of unique shared references of the first kind (combined application of Methods 1 and 2); Share of the joint subarray of unique shared references: the ratio of the total number of nonunique (duplicate) shared references of the second kind, which is supplemented with unique shared references of the first kind, to the total number of nonunique references (combined application of Methods 1 and 2).

REFERENCES

  1. Gilyarevskii, R.S., On the incorrect use of citation indexes for assessment by comparison of science divisions, Autom. Doc. Math. Linguist., 2022, vol. 56, no. 1, pp. 26–29. https://doi.org/10.3103/S000510552201006X

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Funding

The study was performed by the state assignment of the All-Russian Institute of Scientific and Technical Information on the topic FFFU-0003-2022-0007.

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Correspondence to R. S. Gilyarevskii, A. N. Libkind or I. A. Libkind.

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The authors declare that they have no conflicts of interest.

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Translated by L. Solovyova

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Gilyarevskii, R.S., Libkind, A.N. & Libkind, I.A. Classification of Bibliographic References to Determine the Mutual Influence of Large Areas of Knowledge. Autom. Doc. Math. Linguist. 57, 111–126 (2023). https://doi.org/10.3103/S0005105523020061

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  • DOI: https://doi.org/10.3103/S0005105523020061

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