{"title":"文献计量分析一词及其与科学专题中其他高频关键词的交互作用","authors":"Yu. V. Mokhnacheva","doi":"10.3103/S0005105523050060","DOIUrl":null,"url":null,"abstract":"<p>The results of a study of high-frequency key terms in the subject of SciVal (Scopus) are presented, focusing on the term “bibliometric analysis.” The array of high-frequency key terms collected for May to November 2022 from 181 SciVal topics, in which the term “Bibliometric Analysis” appeared as the high-frequency key term, was analyzed by three approximately equal groups of co-words, formed by the number of total intersections in the topics. This division of the high-frequency key terms fits well into S. Bradford’s law, due to which the “core” of the high-frequency key terms was formed on the topics under study. As a result, the topics closest in content were identified. The results of our study form a contribution to the understanding of the relationships between different research topics by analyzing the dynamics of keywords, confirming the hypothesis that using networks of keywords from different disciplines, you can identify common features between them and the number of matches between keywords affects the strength of relationships between topics.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Term “Bibliometric Analysis” and Its Interaction with Other High-Frequency Keywords in the Topics of SciVal\",\"authors\":\"Yu. V. Mokhnacheva\",\"doi\":\"10.3103/S0005105523050060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The results of a study of high-frequency key terms in the subject of SciVal (Scopus) are presented, focusing on the term “bibliometric analysis.” The array of high-frequency key terms collected for May to November 2022 from 181 SciVal topics, in which the term “Bibliometric Analysis” appeared as the high-frequency key term, was analyzed by three approximately equal groups of co-words, formed by the number of total intersections in the topics. This division of the high-frequency key terms fits well into S. Bradford’s law, due to which the “core” of the high-frequency key terms was formed on the topics under study. As a result, the topics closest in content were identified. The results of our study form a contribution to the understanding of the relationships between different research topics by analyzing the dynamics of keywords, confirming the hypothesis that using networks of keywords from different disciplines, you can identify common features between them and the number of matches between keywords affects the strength of relationships between topics.</p>\",\"PeriodicalId\":42995,\"journal\":{\"name\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.3103/S0005105523050060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.3103/S0005105523050060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
The Term “Bibliometric Analysis” and Its Interaction with Other High-Frequency Keywords in the Topics of SciVal
The results of a study of high-frequency key terms in the subject of SciVal (Scopus) are presented, focusing on the term “bibliometric analysis.” The array of high-frequency key terms collected for May to November 2022 from 181 SciVal topics, in which the term “Bibliometric Analysis” appeared as the high-frequency key term, was analyzed by three approximately equal groups of co-words, formed by the number of total intersections in the topics. This division of the high-frequency key terms fits well into S. Bradford’s law, due to which the “core” of the high-frequency key terms was formed on the topics under study. As a result, the topics closest in content were identified. The results of our study form a contribution to the understanding of the relationships between different research topics by analyzing the dynamics of keywords, confirming the hypothesis that using networks of keywords from different disciplines, you can identify common features between them and the number of matches between keywords affects the strength of relationships between topics.
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.