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《Journal of Informetrics》2014,8(2):369-383
Subject classification arises as an important topic for bibliometrics and scientometrics, searching to develop reliable and consistent tools and outputs. Such objectives also call for a well delimited underlying subject classification scheme that adequately reflects scientific fields. Within the broad ensemble of classification techniques, clustering analysis is one of the most successful.Two clustering algorithms based on modularity – the VOS and Louvain methods – are presented here for the purpose of updating and optimizing the journal classification of the SCImago Journal & Country Rank (SJR) platform. We used network analysis and Pajek visualization software to run both algorithms on a network of more than 18,000 SJR journals combining three citation-based measures of direct citation, co-citation and bibliographic coupling. The set of clusters obtained was termed through category labels assigned to SJR journals and significant words from journal titles.Despite the fact that both algorithms exhibited slight differences in performance, the results show a similar behaviour in grouping journals. Consequently, they are deemed to be appropriate solutions for classification purposes. The two newly generated algorithm-based classifications were compared to other bibliometric classification systems, including the original SJR and WoS Subject Categories, in order to validate their consistency, adequacy and accuracy. In addition to some noteworthy differences, we found a certain coherence and homogeneity among the four classification systems analysed. 相似文献
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《Journal of Informetrics》2022,16(1):101241
Usage of field-normalized citation scores is a bibliometric standard. Different methods for field-normalization are in use, but also the choice of field-classification system determines the resulting field-normalized citation scores. Using Web of Science data, we calculated field-normalized citation scores using the same formula but different field-classification systems to answer the question if the resulting scores are different or similar. Six field-classification systems were used: three based on citation relations, one on semantic similarity scores (i.e., a topical relatedness measure), one on journal sets, and one on intellectual classifications. Systems based on journal sets and intellectual classifications agree on at least the moderate level. Two out of the three sets based on citation relations also agree on at least the moderate level. Larger differences were observed for the third data set based on citation relations and semantic similarity scores. The main policy implication is that normalized citation impact scores or rankings based on them should not be compared without deeper knowledge of the classification systems that were used to derive these values or rankings. 相似文献
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在学术期刊的计量评价指标体系中,影响因子和总被引频次是2项最为重要的指标,占据了较高的权重;但是,期刊办刊历史长短、发表论文多少、出版周期长短、学科人群多少等都会影响总被引频次的大小.尤其是一些发表大量低水平论文的期刊,依靠论文数量众多,依然可以获得较高的总被引频次;但其影响因子却很低,论文质量很差.如何客观甄别这类论文数量巨大而质量效益不高的期刊？本文提出一个全新的衡量期刊量效关系的指标——期刊量效指数(journal mass index,JMI).“量”指期刊的发文量,“效”则引入期刊影响因子.JMI定义为某刊影响因子与该刊影响因子对应的发文量的比值,意义是平均每篇文献对该刊影响因子的贡献值.JMI能客观反映同一个学科中量大质低的期刊的“臃肿程度”.在《中国学术期刊影响因子年报(2016版)》中,JMI被应用于修正期刊影响力指数(CI)排序,使CI排序更准确地反映学术期刊的学科影响力排名.实践证明,JMI是一个对学术期刊量效关系进行客观评判的有用的计量指标. 相似文献
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《Journal of Informetrics》2020,14(1):100998
Biomedical research encompasses diverse types of activities, from basic science (“bench”) to clinical medicine (“bedside”) to bench-to-bedside translational research. It, however, remains unclear whether different types of research receive citations at varying rates. Here we aim to answer this question by using a newly proposed paper-level indicator that quantifies the extent to which a paper is basic science or clinical medicine. Applying this measure to 5 million biomedical papers, we find a systematic citation disadvantage of clinical oriented papers; they tend to garner far fewer citations and are less likely to be hit works than papers oriented towards basic science. At the same time, clinical research has a higher variance in its citation. We also find that the citation difference between basic and clinical research decreases, yet still persists, if longer citation-window is used. Given the increasing adoption of short-term, citation-based bibliometric indicators in funding decisions, the under-cited effect of clinical research may provide disincentives for bio-researchers to venture into the translation of basic scientific discoveries into clinical applications, thus providing explanations of reasons behind the existence of the gap between basic and clinical research that is commented as “valley of death” and the commentary of “extinction” risk of translational researchers. Our work may provide insights to policy-makers on how to evaluate different types of biomedical research. 相似文献
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《图书情报工作》论文关键词及分类号的统计分析 总被引：2，自引：0，他引：2
运用文献计量学方法,统计2001-2003年《图书情报工作》论文关键词及分类号,并对其数量、内容、标引质量等进行研究分析。结果显示,该刊关键词和分类号的标引质量较高,但还有不足之处。希望广大论文作者和编辑人员共同努力,进一步提高科技论文的标引质量。 相似文献
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《Journal of Informetrics》2020,14(4):101074
Demonstrating the practical value of public research has been an important subject in science policy. Here we present a detailed study on the evolution of the citation linkage between life science related patents and biomedical research over a 37-year period. Our analysis relies on a newly-created dataset that systematically links millions of non-patent references to biomedical papers. We find a large disparity in the volume of citations to science among technology sectors, with biotechnology and drug patents dominating it. The linkage has been growing exponentially over a long period of time, doubling every 2.9 years. The U.S. has been the largest producer of cited science for years, receiving nearly half of the citations. More than half of citations goes to universities. We use a new paper-level indicator to quantify to what extent a paper is basic research or clinical medicine. We find that the cited papers are likely to be basic research, yet a significant portion of papers cited in patents that are related to FDA-approved drugs are clinical research. The U.S. National Institute of Health continues to be an important funder of cited science. For the majority of companies, more than half of citations in their patents are authored by public research. Taken together, these results indicate a continuous linkage of public science to private sector inventions. 相似文献
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《Journal of Informetrics》2014,8(1):123-135
Journal self-citations strongly affect journal evaluation indicators (such as impact factors) at the meso- and micro-levels, and therefore they are often increased artificially to inflate the evaluation indicators in journal evaluation systems. This coercive self-citation is a form of scientific misconduct that severely undermines the objective authenticity of these indicators. In this study, we developed the feature space for describing journal citation behavior and conducted feature selection by combining GA-Wrapper with RelifF. We also constructed a journal classification model using the logistic regression method to identify normal and abnormal journals. We evaluated the performance of the classification model using journals in three subject areas (BIOLOGY, MATHEMATICS and CHEMISTRY, APPLIED) during 2002–2011 as the test samples and good results were achieved in our experiments. Thus, we developed an effective method for the accurate identification of coercive self-citations. 相似文献
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The purpose of this study is to find a theoretically grounded, practically applicable and useful granularity level of an algorithmically constructed publication-level classification of research publications (ACPLC). The level addressed is the level of research topics. The methodology we propose uses synthesis papers and their reference articles to construct a baseline classification. A dataset of about 31 million publications, and their mutual citations relations, is used to obtain several ACPLCs of different granularity. Each ACPLC is compared to the baseline classification and the best performing ACPLC is identified. The results of two case studies show that the topics of the cases are closely associated with different classes of the identified ACPLC, and that these classes tend to treat only one topic. Further, the class size variation is moderate, and only a small proportion of the publications belong to very small classes. For these reasons, we conclude that the proposed methodology is suitable to determine the topic granularity level of an ACPLC and that the ACPLC identified by this methodology is useful for bibliometric analyses. 相似文献
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国家自然科学基金资助妇产科学课题发文情况分析 总被引：1，自引：0，他引：1
应用文献计量学方法对中国期刊全文数据库（医药卫生专辑）收录的2000—2005年国家自然科学基金（NSFC）资助的妇产科学论文产出情况进行分析和讨论。结果表明,自2000年以来我国相关论文量逐年递增,显示了相关科研的后劲与创新发展态势,其专业分布与我国医学科研领域的重点项目和发展思路一致,但存在着一定程度的地区、机构及期刊分布差异。相关部门应对科研单位的人才培养、人才储备、科研实力、科研管理水平以及激励机制等相关因素进行更深入的分析研究。 相似文献
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This study investigates the use, citation and diffusion of three bibliometric mapping software tools (CiteSpace, HistCite and VOSviewer) in scientific papers. We first conduct a content analysis of a sample of 481 English core journal papers—i.e., papers from journals deemed central to their respective disciplines—in which at least one of these tools is mentioned. This allows us to understand the predominant mention and citation practices surrounding these tools. We then employ several diffusion indicators to gain insight into the diffusion patterns of the three software tools. Overall, we find that researchers mention and cite the tools in diverse ways, many of which fall short of a traditional formal citation. Our results further indicate a clear upward trend in the use of all three tools, though VOSviewer is more frequently used than CiteSpace or HistCite. We also find that these three software tools have seen the fastest and most widespread adoption in library and information science research, where the tools originated. They have since been gradually adopted in other areas of study, initially at a lower diffusion speed but afterward at a rapidly growing rate. 相似文献
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Despite its rising position as a first-class research object, scientific software remains a marginal object in studies of scholarly communication. This study aims to fill the gap by examining the co-mention network of R packages across all Public Library of Science (PLoS) journals. To that end, we developed a software entity extraction method and identified 14,310 instances of R packages across the 13,684 PLoS journal papers mentioning or citing R. A paper-level co-mention network of these packages was visualized and analyzed using three major centrality measures: degree centrality, betweenness centrality, and PageRank. We analyzed the distributive patterns of R packages in all PLoS papers, identified the top packages mentioned in these papers, and examined the clustering structure of the network. Specifically, we found that the discipline and function of the packages can partly explain the largest clusters. The present study offers the first large-scale analysis of R packages’ extensive use in scientific research. As such, it lays the foundation for future explorations of various roles played by software packages in the scientific enterprise. 相似文献
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A systematic empirical comparison of different approaches for normalizing citation impact indicators
We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators. 相似文献
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流行于台湾地区的文献分类法主要有《中国图书分类法》、《中国图书十进分类法》、《佛教图书分类法》3种,这些分类法或由台湾本土发明,或经台湾数次修订,经过近50年发展,分类法厘订之道已渐具台湾特色,研究并归纳这些特色,不仅有助于全面了解台湾地区文献分类法的发展源流,兼且可资大陆地区文献分类法修订时借鉴。 相似文献
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基于F1000与WoS的同行评议与文献计量相关性研究 总被引：1，自引：1，他引：0
为比较同行评议与文献计量方法在科学评价中的有效性及相关性,选取F1000以及Web of Science数据库,采用SPSS16.0软件,将近2000篇论文的F1000因子与Web of Science数据库中指标进行相关性比较。结果显示,F1000因子与统计区间内的被引频次呈显著正相关,同时一些F1000因子很高的论文并没有高频被引,反之亦然。结论指出:从统计学的视角,文献计量指标与同行评议结果具有正向相关性,但是无论是同行评议还是文献计量,单独作为科学评价标准都会有失偏颇,以引文分析为代表的定量指标与同行评议方法的结合将是未来科学评价的主流。 相似文献
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杜定友先生是我国近现代图书馆学的开创者,所著《校仇新义》是其代表作之一,书中对四库分类法的批判惹人瞩目。认为四库分类法过于囿于成见,以至于经无定义,子不成家,史不以时,集而无物,但他并未完全否定四库分类法。主张新的统一分类法必须考虑到中国古籍的特殊性,新旧合流,对四库分类法加以改造,使之更合乎图书分类的实际情况。 相似文献
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Konstantinos Petridis Chrisovalantis Malesios Garyfallos Arabatzis Emmanuel Thanassoulis 《Journal of Informetrics》2013,7(2):505-521
In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score. 相似文献
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以中北大学2000-2009年SCI收录的论文为研究对象,运用文献计量学方法,从论文数量、学科分布、期刊源、影响因子等方面,分析与评价学校的科研水平和发展趋势、学科建设和发展方向、科研力量分布和结构、论文质量和学术水平等,以促进本校科研工作的快速发展。 相似文献
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用传统分类表与叙词表编制TAXONOMY 的理论可行性研究 总被引：2，自引：0，他引：2
Taxonomy概念可以理解为一个用于支持浏览功能的、基于某一特定环境或领域的概念等级体系。它由等级结构和主题词两个基本元素组成,在形式上结合了分类法和叙词表的特点,为用传统分类法和叙词表编制Taxonomy提供了理论可能性。但由于分类法、叙词表和Taxonomy在性质与功能上均有不同之处,在利用传统分类法和叙词表编制Taxonomy过程中会遇到一些问题,首先,分类法和叙词表在主题范覆盖范围方面可能满足不了Taxonomy的要求;其次,分类法和叙词表的两个基本元素,等级结构和主题词在多大程度上可被利用,有待进一步实证。另外,如何将环境因素结合到Taxonomy类表中,是个有待补充的问题。 相似文献