Statistical relationships between corresponding authorship,international co-authorship and citation impact of national research systems

This paper presents a statistical analysis of the relationship between three science indicators applied in earlier bibliometric studies, namely research leadership based on corresponding authorship, international collaboration using international co-authorship data, and field-normalized citation impact. Indicators at the level of countries are extracted from the SIR database created by SCImago Research Group from publication records indexed for Elsevier’s Scopus. The relationship between authorship and citation-based indicators is found to be complex, as it reflects a country’s phase of scientific development and the coverage policy of the database. Moreover, one should distinguish a genuine leadership effect from a purely statistical effect due to fractional counting. Further analyses at the level of institutions and qualitative validation studies are recommended.     

地名拼写的汉语拼音化 ——科技期刊出版中不可忽略的一个爱国细节

我国政府规定采用汉语拼音方案拼写中国地名,取代旧式威妥玛式拼写方案;然而,国内科技期刊对中国地名采用威妥玛式拼写仍然不在少数.例如“长江”,很多刊物仍采用威妥玛式方案,拼写成“Yangtze”.而对国外主流刊物初步调研显示,国外的学者和出版物不仅接受而且理解认同中国地名的汉语拼音法.作者认为,我国地名的威妥玛式拼写是殖民地半殖民地化的产物,是我国积贫积弱的时代标志,地名拼写的汉语拼音化是我国科技期刊出版中不可忽略的一个爱国细节,应该严格把关.     

Improving the reliability of short-term citation impact indicators by taking into account the correlation between short- and long-term citation impact

The normalized citation indicator may not be sufficiently reliable when a short citation time window is used, because the citation counts for recently published papers are not as reliable as those for papers published many years ago. In a limited time period, recent publications usually have insufficient time to accumulate citations and the citation counts of these publications are not sufficiently reliable to be used in the citation impact indicators. However, normalization methods themselves cannot solve this problem. To solve this problem, we introduce a weighting factor to the commonly used normalization indicator Category Normalized Citation Impact (CNCI) at the paper level. The weighting factor, which is calculated as the correlation coefficient between citation counts of papers in the given short citation window and those in the fixed long citation window, reflects the degree of reliability of the CNCI value of one paper. To verify the effect of the proposed weighted CNCI indicator, we compared the CNCI score and CNCI ranking of 500 universities before and after introducing the weighting factor. The results showed that although there was a strong positive correlation before and after the introduction of the weighting factor, some universities’ performance and rankings changed dramatically.     

Network assembly of scientific communities of varying size and specificity

How does the collaboration network of researchers coalesce around a scientific topic? What sort of social restructuring occurs as a new field develops? Previous empirical explorations of these questions have examined the evolution of co-authorship networks associated with several fields of science, each noting a characteristic shift in network structure as fields develop. Historically, however, such studies have tended to rely on manually annotated datasets and therefore only consider a handful of disciplines, calling into question the universality of the observed structural signature. To overcome this limitation and test the robustness of this phenomenon, we use a comprehensive dataset of over 189,000 scientific articles and develop a framework for partitioning articles and their authors into coherent, semantically related groups representing scientific fields of varying size and specificity. We then use the resulting population of fields to study the structure of evolving co-authorship networks. Consistent with earlier findings, we observe a global topological transition as the co-authorship networks coalesce from a disjointed aggregate into a dense giant connected component that dominates the network. We validate these results using a separate, complimentary corpus of scientific articles, and, overall, we find that the previously reported characteristic structural evolution of a scientific field's associated co-authorship network is robust across a large number of scientific fields of varying size, scope, and specificity. Additionally, the framework developed in this study may be used in other scientometric contexts in order to extend studies to compare across a larger range of scientific disciplines.     

Multivariate approach to classify research institutes according to their outputs: The case of the CSIC's institutes

This paper attempts to build a classification model according to the research products created by those institutes and hence to design specific evaluation processes. Several scientific input/output indicators belonging to 109 research institutes from the Spanish National Research Council (CSIC) were selected. A multidimensional approach was proposed to resume these indicators in various components. A clustering analysis was used to classify the institutes according to their scores with those components (principal component analysis). Moreover, the validity of the a priori classification was tested and the most discriminant variables were detected (linear discriminant analysis). Results show that there are three types of institutes according to their research outputs: Humanistic, Scientific and Technological. It is argue that these differences oblige to design more precise assessment exercises which focus on the particular results of each type of institute. We conclude that this method permits to build more precise research assessment exercises which consider the varied nature of the scientific activity.     

国外图书馆员工作评估体系介绍及其特点研究

本文运用实例对国外图书馆员工作评估体系的内容、框架格式等进行了简单的介绍,并通过对其特点及应用的分析,使我们可以借鉴其长处完善我们自身的工作评估体系从而达到推动图书馆工作发展的目的。     

A comparative study of cross-domain research output and citations: Research impact cubes and binary citation frequencies

Across the various scientific domains, significant differences occur with respect to research publishing formats, frequencies and citing practices, the nature and organisation of research and the number and impact of a given domain's academic journals. Consequently, differences occur in the citations and h-indices of the researchers. This paper attempts to identify cross-domain differences using quantitative and qualitative measures. The study focuses on the relationships among citations, most-cited papers and h-indices across domains and for research group sizes. The analysis is based on the research output of approximately 10,000 researchers in Slovenia, of which we focus on 6536 researchers working in 284 research group programmes in 2008–2012.As comparative measures of cross-domain research output, we propose the research impact cube (RIC) representation and the analysis of most-cited papers, highest impact factors and citation distribution graphs (Lorenz curves). The analysis of Lotka's model resulted in the proposal of a binary citation frequencies (BCF) distribution model that describes well publishing frequencies. The results may be used as a model to measure, compare and evaluate fields of science on the global, national and research community level to streamline research policies and evaluate progress over a definite time period.     

慎重对待科技论文署名等变更 ——以《高等学校化学学报》和《高等学校化学研究》期刊工作为例

近年来,科技论文投稿后作者要求对论文署名变更、署名顺序变更及单位变更的情况越来越多.本文结合工作实例分析了作者提出署名等变更的原因,发现不合理署名变更的根源是作者忽视版权法及不了解"不当署名"为严重学术问题.提出了避免科技论文署名等更改有效方法,指出对作者版权教育的重要性.建议科技期刊编辑部建立固定的工作流程处理作者提出的变更申请,并根据原则和实际情况妥善解决此类问题.     

学者研究主题演化的时空测度:速度、覆盖度和迂回度

[目的/意义]运用深度学习技术,提出结合时间和空间特征的测度(速度、覆盖度和迂回度)方法,用于量化学者研究主题演化,从而为基于内容的学者评价提供量化依据。[方法/过程]提出三维指标框架,其中速度反映作者改变研究主题快慢的平均程度,覆盖度反映作者研究内容所覆盖的主题广度,迂回度反映作者研究路径的曲折性。使用微软学术数据集中计算机科学的作者进行实证研究,并考察学者研究主题演化的三维测度和学者学术影响力和生产力的关系。[结果/结论] 实证研究结果显示,覆盖度与总被引量和总发文量的关系为单调递减,这一特征说明聚焦于特定研究主题较为深入的作者,其发文量和影响力都较大。作者研究主题演化的"速度"和"迂回度"与总被引量、总发文量都存在先增加后减少的倒U型关系。所提出的多维度指标框架不仅可在理论上丰富科学计量学对于学者研究主题转移演化及其机制的理解,而且结合深度学习模型提出了问题的解决思路。     

科技期刊中刊名人名地名汉语拼音存在问题分析

从100种科技期刊的刊名、人名、地名汉语拼音拼写情况的调查结果看出,有的期刊能按国家标准拼写,有的期刊没有达到标准要求.对存在的问题进行了分析.     

Revisiting the scientometric conceptualization of impact and its measurement

The development of scientometric indicators and methods for evaluative purposes, requires a multitude of assumptions, conventions, limitations, and caveats. Given this, we cannot permit ambiguities in the key concepts forming the basis of scientometric science itself, or research assessment exercises would rest on quicksand. This conceptual work attempts to spell out some principles leading to a clear definition of “impact” of research, and above all, of the appropriate scientometric indicator to measure it. The aim is to stimulate a discussion aimed at a definitive convergence on the meaning and measurement of a fundamental concept of the scientometric science.     

引文分析学形成与发展的可视化分析

以引文分析领域的1 906篇论文、65 426条引文为研究对象,借助知识计量和知识图谱及先进的可视化技术CiteSpace等软件工具,绘制引文分析领域的发展趋势知识图谱,揭示引文分析领域的初始形成期、发展繁荣期、深化拓张期三个阶段的演进历程;通过加菲尔德、普赖斯、斯莫尔等主要代表人物文献的可视化图谱,具体呈现出他们各自在不同时期对引文分析领域发展的独特贡献以及他们有关引文分析的经典文献对引文分析领域演化路径的关键作用。     

Comparison of research performance of Italian and Norwegian professors and universities

This is the first ever attempt of application in a country other than Italy of the output-to-input indicator FSS, to assess and compare the research performance of professors and universities, within and between countries. A special attention has been devoted to the presentation of the methodology developed to set up a common field classification scheme of professors, and to overcome the limited availability of comparable input data. Results of the comparison between countries, carried out in the 2011–2015 period, show similar average performances of professors, but noticeable differences in the distributions, whereby Norwegian professors are more concentrated in the tails. Norway shows notable higher performance in Mathematics and Earth and Space Sciences, while Italy in Biomedical Research and Engineering.     

Empirical study of L-Sequence: The basic h-index sequence for cumulative publications with consideration of the yearly citation performance

Most current h-type indicators use only a single number to measure a scientist's productivity and impact of his/her published works. Although a single number is simple to calculate, it fails to outline his/her academic performance varying with time. We empirically study the basic h-index sequence for cumulative publications with consideration of the yearly citation performance (for convenience, referred as L-Sequence). L-Sequence consists of a series of L factors. Based on the citations received in the corresponding individual year, every factor along a scientist's career span is calculated by using the h index formula. Thus L-Sequence shows the scientist's dynamic research trajectory and provides insight into his/her scientific performance at different periods. Furthermore, L_∝, summing up all factors of L-Sequence, is for the evaluation of the whole research career as alternative to other h-index variants. Importantly, the partial factors of the L-Sequence can be adapted for different evaluation tasks. Moreover, L-Sequence could be used to highlight outstanding scientists in a specific period whose research interests can be used to study the history and trends of a specific discipline.     

科学计量学主流研究领域与热点前沿研究

[目的/意义]基于对《科学计量学》杂志的研究与回顾,找出科学计量学领域进入发展时期后的主流研究领域和热点前沿,探究其演进脉络,并绘制可视化的知识图谱。[方法/过程]借助Bibexcel与SPSS软件,通过共引分析与因子分析法,得出科学计量学在各发展阶段的主流研究领域;通过共词分析法,利用CiteSpace II软件,对科学计量学3个阶段的研究热点与前沿分别进行识别与可视化。[结果/结论]引文分析、科学合作、科研评价一直是科学计量学在发展时期的主流研究领域,科学计量学的研究对象不断扩充,研究方法不断完善,并逐渐引入社会网络分析等其他学科方法;随着发展阶段的推移,研究热点与前沿的网络密度不断提高,研究前沿动态转变过程中的转折点也不断增加,科学计量学领域的研究更加丰富和深入。创新性地对科学计量学的主流研究领域和热点前沿进行分阶段分析,可以更清晰地展示出发展时期科学计量学的演进脉络。     

医学论文作者单位标注问题探讨

近年来,多作者、多单位署名已成为科技论文署名的新趋势.作者单位标注关系到论文责任单位的知识产权.研究生、进修医师论文发表、作者工作单位变更以及多单位间合作是出现作者单位标注不当的常见原因.期刊编辑加强对作者来稿的审查,提高作者的知识产权意识,有助于避免作者单位标注不当的发生.     

Using genderize.io to infer the gender of first names: how to improve the accuracy of the inference

Objective:We recently showed that genderize.io is not a sufficiently powerful gender detection tool due to a large number of nonclassifications. In the present study, we aimed to assess whether the accuracy of inference by genderize.io can be improved by manipulating the first names in the database.Methods:We used a database containing the first names, surnames, and gender of 6,131 physicians practicing in a multicultural country (Switzerland). We uploaded the original CSV file (file #1), the file obtained after removing all diacritic marks, such as accents and cedilla (file #2), and the file obtained after removing all diacritic marks and retaining only the first term of the compound first names (file #3). For each file, we computed three performance metrics: proportion of misclassifications (errorCodedWithoutNA), proportion of nonclassifications (naCoded), and proportion of misclassifications and nonclassifications (errorCoded).Results:naCoded, which was high for file #1 (16.4%), was reduced after data manipulation (file #2: 11.7%, file #3: 0.4%). As the increase in the number of misclassifications was small, the overall performance of genderize.io (i.e., errorCoded) improved, especially for file #3 (file #1: 17.7%, file #2: 13.0%, and file #3: 2.3%).Conclusions:A relatively simple manipulation of the data improved the accuracy of gender inference by genderize.io. We recommend using genderize.io only with files that were modified in this way.     

论文作者将栏目名称误认为期刊名称的现象及其应对策略

指出参考文献中存在将栏目名称误认为期刊名称的现象,分析其形成的原因和存在的危害.认为科技期刊应采取规范科技期刊的编排格式、加强参考文献的编辑加工、实行参考文献的专业核查等措施加以防范.     

Predicting the Q of junior researchers using data from the first years of publication

A researcher's Q denotes their ability in scientific research as a real number. Due to their short presence in the academic environment, junior researchers have unstable Q values. This article aims to present a model that uses data from junior researchers’ first years of publication to predict their stable Q values. We tested the deep model and the linear regression model and compared their accuracies. We have obtained reliable results showing that the predicted values estimated with both models are better than the estimated Q values computed with the Q model itself when using only data from the first five years of publication. Lastly, we note that both approaches are robust approaches to deal with the inflation of citation bias.     

A novel methodology to assess the scientific standing of nations at field level

The formulation of national research policies would benefit greatly from reliable strategic analysis of the scientific infrastructure, aimed at identifying the relevant strengths and weaknesses at field level. Bibliometric methodologies thus far proposed in the literature are not completely satisfactory. This work proposes a novel “output-to-input-oriented” approach, which permits identification of research strengths and weaknesses on the basis of the ratios of top scientists and highly cited articles to research expenditures in each field. The proposed approach is applied to the Italian academic system. 2012–2016 scientific publications are analyzed, in the 218 research fields where bibliometric assessment is appropriate.