Qualitative and Quantitative Analysis of the Publication Activity of Russian Research Institutions in the Field of Appli
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Qualitative and Quantitative Analysis of the Publication Activity of Russian Research Institutions in the Field of Applied Chemistry V. V. Korolevaa, O. V. Ivanova, A. A. Vedyagina,b,*, A. S. Lyadova,c, A. V. Leonidova, and A. V. Kolobova Lebedev Physical Institute, Russian Academy of Sciences, Moscow, 119991 Russia Boreskov Institute of Catalysts, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090 Russia c Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Moscow, 119991 Russia *e-mail: [email protected] a
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Received August 21, 2020; revised August 21, 2020; accepted August 25, 2020
Abstract—Qualitative and quantitative analysis of the publication activity of chemical institutions of the Russian Academy of Sciences within the jurisdiction of the Ministry of Science and Higher Education of the Russian Federation in the period 2015–2019 in the field of applied chemistry was performed. The Web of Science database was used as the information source. Analysis was performed using the Zerkalo (Mirror) intellectual system for analysis and prediction of the research activity, developed by the Lebedev Physical Institute, Russian Academy of Sciences. The most significant keywords that largely characterize promising directions in the field of applied chemistry were revealed. The publication effectiveness of research institutions was analyzed by the method of fractional counting with differentiation of contributions from articles. The localization analysis of publications was performed on the basis of the affiliation data indicated in the papers. It revealed stable international cooperation for one third of research teams. Keywords: effectiveness in research activity, fractional counting, complex index of publication effectiveness (CIPE), Web of Science database DOI: 10.1134/S1070427220090037
INTRODUCTION Methods of artificial intellect for analysis of data sets, including “big data,” in various fields of human activity became more widely used and more demanded recently owing to the intense progress of methods of mathematical statistics and optimization and of algorithms of operation with digital data, and also to expansion of applications of the graph theory. One of the most frequently used applications of these methods in evaluation of the research activity is analysis of the publication activity in one or another field [1–5]. Detailed analysis can be used for determining new trends in the development of science and engineering and for revealing emerging research directions, on the one hand, and for evaluating the effectiveness of institutions, research teams, and separate researchers, on the other hand [6].
Among the existing worldwide databases, the Web of Science and Scopus platforms are the most popular [7, 8]. They combine the databases of abstracts of papers published in the scientific periodicals, including databases on mutual citation of papers. The information collected in these databases is the most complete for evaluating the citation index based on alternative databases [Russ
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