排名靠前的大学发表的科学论文中,机构间和机构内的多归属作者

IF 3.5 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Chi-shiou Lin , Mu-hsuan Huang , Dar-zen Chen
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引用次数: 0

摘要

科学作者的多隶属关系现象在学术交流中越来越受到关注。本研究考察了多隶属关系的范围和影响,区分了机构内和机构间的多隶属关系,包括基于国家和国际隶属关系的亚型。该研究利用科学网的数据,分析了十年间(2013-2022年)全球排名靠前的大学发表的科学论文。结果表明,多重隶属关系非常普遍,有22.54%的作者和超过一半的论文至少表现出一次多重隶属关系。研究发现,不同国家和学科领域的多隶属关系趋势存在显著差异。研究结果提出了关于多隶属关系对研究评估和大学排名的影响的关键问题,表明需要对隶属关系进行精确的文献计量措施和作者指导,以解释这一日益增长的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The inter-institutional and intra-institutional multi-affiliation authorships in the scientific papers produced by the well-ranked universities
The phenomenon of multi-affiliation in scientific authorship has increasingly garnered attention in scholarly communication. This study examines the extent and implications of multi-affiliation, distinguishing between intra-institutional and inter-institutional multi-affiliations, including their subtypes based on national and international affiliations. Utilizing data from the Web of Science, the study analyzes scientific papers from well-ranked global universities over a decade (2013–2022). The results indicate a significant prevalence of multi-affiliation, with 22.54 % of authorships and over half of the papers exhibiting at least one instance of multi-affiliation. The study finds notable variations in multi-affiliation trends across countries and subject fields. The findings raise critical questions about the impact of multi-affiliation on research evaluation and university rankings, suggesting a need for refined bibliometric measures and author guidance on affiliations to account for this growing trend.
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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
期刊介绍: Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.
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