“经济景观”一词使用的科学分析

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2023-04-18 DOI:10.3103/S0005105523010053
V. A. Blaginin, M. N. Goncharova, E. V. Sokolova
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引用次数: 1

摘要

这项工作的目的是介绍对“经济景观”一词的文献计量数据的分析结果,以确定知识生成的中心,并评估其知识和相关性。作为这项研究的一部分,提出了一个假设,即对所提出的科学术语缺乏应有的关注。计算基于对书目数据的科学计量分析方法,以确定科学出版物在时间和空间上的数量和分布。这项工作也使用了制图方法。科学电子图书馆eLIBRARY.Ru的书目基础和Scopus数据库中的出版物库被用作数据源。在研究过程中,确定了内部研究前沿,并对科学出版物进行了审查。得出的结论是,不同学科的代表对所研究的主题越来越感兴趣。这项研究的结果可能会引起经济学家和科学计量学领域专家的兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Scientometric Analysis of the Use of the Term “Economic Landscape”

The purpose of this work is to present the results of the analysis of bibliometric data on the term “economic landscape” in order to identify centers of knowledge generation and to assess its knowledge and relevance. As part of this study, a hypothesis was put forward regarding the lack of due attention to the presented scientific term. The calculations are based on the methods of scientometric analysis of bibliographic data to determine the volume and distribution of scientific publications across time and space. Cartography methods were also used in this work. The bibliographic basis of the scientific electronic library eLIBRARY.Ru and the pool of publications in the Scopus database were taken as a data source. In the course of the study, internal research fronts were identified, and an examination of scientific publications was carried out. Conclusions are drawn regarding the growing interest of representatives of different branches of knowledge in the topic under study. The results of the study may be of interest to both economists and specialists in the field of scientometrics.

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来源期刊
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS
AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
40.00%
发文量
18
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.
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