Trends in the Publication Activity of Russian Organizations from 2000 to 2019

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2022-10-04 DOI:10.3103/S0005105522040070

P. Yu. Blinov, D. V. Kosyakov, A. V. Malysheva, A. E. Guskov

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引用次数: 0

Abstract

As has been noted on numerous occasions, between 2012 and 2021, the pace of publications by Russian researchers rapidly increased; however, this growth was uneven in both quantitative and qualitative terms. Moreover, some research organizations had zero or even negative publication activity growth. To achieve a full understanding of the real development processes of the research sector requires analysis of the dynamics of dozens of indicators for hundreds of organizations. However, the question remains: how can these numerous data series be studied? To address this problem, this article proposes a method of classifying trends in time series based on a combination of three statistical tests of randomness against trend: the Cox-Stuart test, the inversion test of randomness, and the Mann–Kendall test. The method is used to classify a series of scientometric parameters that characterize various aspects of the publication activity of 701 leading Russian research organizations and universities, including a comprehensive publication score (an analogue of the official Composite Score for Publication Performance (CSPP)), the average quality level of publications, and the share of articles in conference proceedings. The differences trends of organizations of different types and performance categories are identified. This information is used to formulate new questions for further research into the causes of the observed trends in the development of Russian science.

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2000年至2019年俄罗斯组织出版活动趋势

摘要正如人们多次指出的那样，在2012年至2021年间，俄罗斯研究人员的出版速度迅速加快；然而，这种增长在数量和质量上都是不均衡的。此外，一些研究机构的出版活动增长为零甚至为负。为了充分了解研究部门的实际发展过程，需要对数百个组织的数十项指标的动态进行分析。然而，问题仍然存在：如何研究这些众多的数据系列？为了解决这个问题，本文提出了一种基于三种随机性对趋势的统计检验的时间序列趋势分类方法：Cox-Stuart检验、随机性反演检验和Mann–Kendall检验。该方法用于对一系列科学计量学参数进行分类，这些参数表征了701所俄罗斯领先研究机构和大学出版活动的各个方面，包括综合出版得分（类似于官方出版绩效综合得分（CSPP））、出版物的平均质量水平，以及文章在会议记录中的份额。确定了不同类型和绩效类别的组织的差异趋势。这些信息被用来提出新的问题，以便进一步研究俄罗斯科学发展趋势的原因。

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来源期刊

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-

自引率

40.00%

发文量

期刊介绍： Automatic Documentation and Mathematical Linguistics is an international peer reviewed journal that covers all aspects of automation of information processes and systems, as well as algorithms and methods for automatic language analysis. Emphasis is on the practical applications of new technologies and techniques for information analysis and processing.