Top

Hint

Swipe to navigate through the articles of this issue

Published in:

01-02-2022 | INFORMATION ANALYSIS

Prospective Scientific Research Trend Identification Methods (Based on the Analysis of Gas Fuel-Related Publications)

Authors: Iu. I. Butenko, I. N. Telnova, V. V. Garazha

Published in: Automatic Documentation and Mathematical Linguistics | Issue 1/2022

Abstract

This article reviews prospective scientific research-trend identification methods based on the analysis of scientific publications focused on compressed natural gas. The methods for identifying publication directions and patterns by popularity of separate topics within one subject area are presented. The materials used in the article consist of scientific research on natural gas available in citation databases of Russian Science Citation Index (RSCI), Scopus, and Web of Science and the data from the EGISU R&D system of Russian researches. The results were processed in the VOSviewer software.

previous article Indexing Languages for Digital Humanities

next article On the Incorrect Use of Citation Indices for Assessment by Comparison of Divisions of Science

Makri, A., Pakistan and Egypt had highest rises in research output in 2018, Nature, 2018. https://doi.org/10.1038/d41586-018-07841-9

Sushentsova, N.V. and Chekalina, T.A., Open access scientific electronic libraries, Obraz. Kar’era. Obshchestvo, 2013, no. 4-1, pp. 31–34.

Birkle, C., Pendlebury, Schnell, J., and Adams, J. Web of Science as a data source for research on scientific and scholarly activity, Quant. Sci. Stud., 2020, vol. 1, no. 1, pp. 363–376. https://doi.org/10.1162/qss_a_00018 CrossRef

Mongeon, P. and Paul-Hus, A., The journal coverage of web of science and scopus: a comparative analysis, Scientometrics, 2016, vol. 106, no. 1, pp. 213–228. https://doi.org/10.1007/s11192-015-1765-5 CrossRef

Savel’eva, Yu.V. and Khoperskov, A.V., Scientific journals and efficiency of scientific work: Search systems and databases, Upr. Bol’shimi Sist.: Sb. Trudov, 2013, no. 44, pp. 381–407.

Van Eck, N.J. and Waltman, L., VOSviewer Manual, Leiden: Univ. Leiden, 2013, vol. 1, no. 1, pp. 1–53.

Butenko, Yu.I., Nikolaeva, N.S., and Margaryan, T.D., Structural models of terminological word combinations for marking up a corpus of scientific and technical texts, Vestn. Novosib. Gos. Univ. Ser.: Lingvist. Mezhkul’turnaya Kommun., 2021, vol. 19, no. 3, pp. 46–56. https://doi.org/10.25205/1818-7935-2021-19-3-45-56 CrossRef

Sidnyaev, N.I., Butenko, Yu.I., and Bolotova, E.E., Formal grammar theory in recognition methods of unknown objects, Autom. Doc. Math. Linguist., 2020, vol. 54, pp. 215–225. https://doi.org/10.3103/S000510552004007X CrossRef

Sidnyaev, N.I., Butenko, Ju.I., and Garazha, V.V., Mathematical apparatus for engineering-linguistic models, AIP Conf. Proc., 2019, vol. 2195, p. 020033. https://doi.org/10.1063/1.5140133 CrossRef

10.

Melnikov, A.K. and Ronzhin, A.F., Generalized statistical method of text analysis based on calculation of probability distributions of statistical values, Inf. Ee Prim., 2016, vol. 10, no. 4, pp. 89–95. https://doi.org/10.14357/19922264160409 CrossRef

11.

Volkov, A.V., Peculiarities of computer processing of scientific text, Upr. Innovatsiyami: Teoriya, Metodol., Prakt., 2013, no. 5, pp. 144–151.

12.

Yatsko, V.A., Algorithms and programs for automatic text processing, Vestn. Irkut. Gos. Lingvist. Univ., 2012, vol. 1, no. 17, pp. 150–160.

13.

Pronin, E.N., Africa: Gas-engine fuel market development, Transp. Al’ternativnom Toplive, 2014, no. 3, pp. 68–71.

14.

Tollefson, J., World’s carbon emissions set to spike by 2% in 2017, Nature, 2017, vol. 551, p. 283. https://doi.org/10.1038/nature.2017.22995 CrossRef

15.

Randles, B.M., Pasquetto, I.V., Golshan, M.S., and Borgman, C.L., Using the Jupyter notebook as a tool for open science: An empirical study, ACM/IEEE Joint Conf. on Digital Libraries (JCDL), Toronto, 2017, IEEE, 2017, pp. 1–2. https://doi.org/10.1109/JCDL.2017.7991618

Title: Prospective Scientific Research Trend Identification Methods (Based on the Analysis of Gas Fuel-Related Publications)
Authors: Iu. I. Butenko
I. N. Telnova
V. V. Garazha
Publication date: 01-02-2022
Publisher: Pleiades Publishing
Published in: Automatic Documentation and Mathematical Linguistics / Issue 1/2022
Print ISSN: 0005-1055
Electronic ISSN: 1934-8371
DOI: https://doi.org/10.3103/S0005105522010034

Springer Professional

Hint

Swipe to navigate through the articles of this issue

Prospective Scientific Research Trend Identification Methods (Based on the Analysis of Gas Fuel-Related Publications)

Abstract

Premium Partner

Springer Professional

Hint

Swipe to navigate through the articles of this issue

Abstract

Please log in to get access to this content

Other articles of this Issue 1/2022

Indexing Languages for Digital Humanities

Structural and Functional Modeling of Processes with a Dedicated Control Subject

On the Incorrect Use of Citation Indices for Assessment by Comparison of Divisions of Science

Predicting the Development of Scientific Trends on the Basis of Analysis of Conflicts between Fields of Knowledge

An Adaptive Data-Exchange System

Premium Partner