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1.
Using an initial dataset consisting of 18.5 million distinct authors and 15 million distinct articles published in the period 2000–2016, which are classified into 29 broad scientific fields, we search for regularities at the individual level for very productive authors with citation distributions of a certain size, and for the existence of a macro-micro relationship between the skewness of a scientific field citation distribution and the characteristics of the individual citation distributions of the authors belonging to the field. Our main results are the following three. Firstly, although the skewness of individual citation distributions varies greatly within each field, their average skewness is of a similar order of magnitude in all fields. Secondly, as in the previous literature, field citation distributions are highly skewed and the degree of skewness is very similar across fields. Thirdly, the skewness of field citation distributions is essentially explained in terms of the average skewness of individual authors, as well as individuals’ differences in mean citation rates and the number of publications per author. These results have important conceptual and practical consequences: to understand the skewness of field citation distributions at any aggregate level we must simply explain the skewness of the individual citation distributions of their very productive authors. 相似文献
2.
科学研究的目的在于创造知识,并应用理论成果解决我国社会、经济、文化等发展中的实际问题。将论文发表在国际期刊上可以让更多的国际同行了解我国最新的科研成果,为我国获得更多的国际影响力,所以在过去二十多年里SCI论文成为我国科研考核的一个重要指标。在这种科研评价导向下,我国学者发表的国际论文数量已居世界第一位,而大量来自国内同行的引用使得我国国际论文的被引量排名世界第二。本文提取1990至2015年Web of Science论文及其引文的数据,分析不同国家、不同学科在国家层次的自引情况,并在不同国家、不同学科之间进行比较。研究发现,在排除国内同行的自引后,我国国际论文的真实国际影响力仍然有限,除了临床医学和物理等少数学科外,其他学科仍然低于全球平均水平。 相似文献
3.
The problem of citation impact assessments for recent publication years in institutional evaluations
Lutz Bornmann 《Journal of Informetrics》2013,7(3):722-729
Bibliometrics has become an indispensable tool in the evaluation of institutions (in the natural and life sciences). An evaluation report without bibliometric data has become a rarity. However, evaluations are often required to measure the citation impact of publications in very recent years in particular. As a citation analysis is only meaningful for publications for which a citation window of at least three years is guaranteed, very recent years cannot (should not) be included in the analysis. This study presents various options for dealing with this problem in statistical analysis. The publications from two universities from 2000 to 2011 are used as a sample dataset (n = 2652, univ 1 = 1484 and univ 2 = 1168). One option is to show the citation impact data (percentiles) in a graphic and to use a line for percentiles regressed on ‘distant’ publication years (with confidence interval) showing the trend for the ‘very recent’ publication years. Another way of dealing with the problem is to work with the concept of samples and populations. The third option (very related to the second) is the application of the counterfactual concept of causality. 相似文献
4.
In this study we map out the large-scale structure of citation networks of science journals and follow their evolution in time by using stochastic block models (SBMs). The SBM fitting procedures are principled methods that can be used to find hierarchical grouping of journals that show similar incoming and outgoing citations patterns. These methods work directly on the citation network without the need to construct auxiliary networks based on similarity of nodes. We fit the SBMs to the networks of journals we have constructed from the data set of around 630 million citations and find a variety of different types of groups, such as communities, bridges, sources, and sinks. In addition we use a recent generalization of SBMs to determine how much a manually curated classification of journals into subfields of science is related to the group structure of the journal network and how this relationship changes in time. The SBM method tries to find a network of blocks that is the best high-level representation of the network of journals, and we illustrate how these block networks (at various levels of resolution) can be used as maps of science. 相似文献
5.
In citation network analysis, complex behavior is reduced to a simple edge, namely, node A cites node B. The implicit assumption is that A is giving credit to, or acknowledging, B. It is also the case that the contributions of all citations are treated equally, even though some citations appear multiply in a text and others appear only once. In this study, we apply text-mining algorithms to a relatively large dataset (866 information science articles containing 32,496 bibliographic references) to demonstrate the differential contributions made by references. We (1) look at the placement of citations across the different sections of a journal article, and (2) identify highly cited works using two different counting methods (CountOne and CountX). We find that (1) the most highly cited works appear in the Introduction and Literature Review sections of citing papers, and (2) the citation rankings produced by CountOne and CountX differ. That is to say, counting the number of times a bibliographic reference is cited in a paper rather than treating all references the same no matter how many times they are invoked in the citing article reveals the differential contributions made by the cited works to the citing paper. 相似文献
6.
Modeling a century of citation distributions 总被引：1，自引：1，他引：0
The prevalence of uncited papers or of highly cited papers, with respect to the bulk of publications, provides important clues as to the dynamics of scientific research. Using 25 million papers and 600 million references from the Web of Science over the 1900–2006 period, this paper proposes a simple model based on a random selection process to explain the “uncitedness” phenomenon and its decline over the years. We show that the proportion of cited papers is a function of (1) the number of articles available (the competing papers), (2) the number of citing papers and (3) the number of references they contain. Using uncitedness as a departure point, we demonstrate the utility of the stretched-exponential function and a form of the Tsallis q-exponential function to fit complete citation distributions over the 20th century. As opposed to simple power-law fits, for instance, both these approaches are shown to be empirically well-grounded and robust enough to better understand citation dynamics at the aggregate level. On the basis of these models, we provide quantitative evidence and provisional explanations for an important shift in citation practices around 1960. We also propose a revision of the “citation classic” category as a set of articles which is clearly distinguishable from the rest of the field. 相似文献
7.
《Journal of Informetrics》2014,8(3):683-692
This paper explores a possible approach to a research evaluation, by calculating the renown of authors of scientific papers. The evaluation is based on the citation analysis and its results should be close to a human viewpoint. The PageRank algorithm and its modifications were used for the evaluation of various types of citation networks. Our main research question was whether better evaluation results were based directly on an author network or on a publication network. Other issues concerned, for example, the determination of weights in the author network and the distribution of publication scores among their authors. The citation networks were extracted from the computer science domain in the ISI Web of Science database. The influence of self-citations was also explored. To find the best network for a research evaluation, the outputs of PageRank were compared with lists of prestigious awards in computer science such as the Turing and Codd award, ISI Highly Cited and ACM Fellows. Our experiments proved that the best ranking of authors was obtained by using a publication citation network from which self-citations were eliminated, and by distributing the same proportional parts of the publications’ values to their authors. The ranking can be used as a criterion for the financial support of research teams, for identifying leaders of such teams, etc. 相似文献
8.
《Journal of Informetrics》2019,13(2):738-750
An aspect of citation behavior, which has received longstanding attention in research, is how articles’ received citations evolve as time passes since their publication (i.e., citation ageing). Citation ageing has been studied mainly by the formulation and fit of mathematical models of diverse complexity. Commonly, these models restrict the shape of citation ageing functions and explicitly take into account factors known to influence citation ageing. An alternative—and less studied—approach is to estimate citation ageing functions using data-driven strategies. However, research following the latter approach has not been consistent in taking into account those factors known to influence citation ageing. In this article, we propose a model-free approach for estimating citation ageing functions which combines quantile regression with a non-parametric specification able to capture citation inflation. The proposed strategy allows taking into account field of research effects, impact level effects, citation inflation effects and skewness in the distribution of cites effects. To test our methodology, we collected a large dataset consisting of more than five million citations to 59,707 research articles spanning 12 dissimilar fields of research and, with this data in hand, tested the proposed strategy. 相似文献
9.
《Journal of Informetrics》2020,14(3):101039
Predicting the citation counts of academic papers is of considerable significance to scientific evaluation. This study used a four-layer Back Propagation (BP) neural network model to predict the five-year citations of 49,834 papers in the library, information and documentation field indexed by the CSSCI database and published from 2000 to 2013. We extracted six paper features, two journal features, nine author features, eight reference features, and five early citation features to make the prediction. The empirical experiments showed that the performance of the BP neural network is significantly better than those of the six baseline models. In terms of the prediction effect, the accuracy of the model at predicting infrequently cited papers was higher than that for frequently cited ones. We determined that five essential features have significant effects on the prediction performance of the model, i.e., ‘citations in the first two years’, ‘first-cited age’, ‘paper length’, ‘month of publication’, and ‘self-citations of journals’, and the other features contribute only slightly to the prediction. 相似文献
10.
《Journal of Informetrics》2020,14(2):101013
A citation is a well-established mechanism for connecting scientific artifacts. Citation networks are used by citation analysis for a variety of reasons, prominently to give credit to scientists’ work. However, because of current citation practices, scientists tend to cite only publications, leaving out other types of artifacts such as datasets. Datasets then do not get appropriate credit even though they are increasingly reused and experimented with. We develop a network flow measure, called DataRank, aimed at solving this gap. DataRank assigns a relative value to each node in the network based on how citations flow through the graph, differentiating publication and dataset flow rates. We evaluate the quality of DataRank by estimating its accuracy at predicting the usage of real datasets: web visits to GenBank and downloads of Figshare datasets. We show that DataRank is better at predicting this usage compared to alternatives while offering additional interpretable outcomes. We discuss improvements to citation behavior and algorithms to properly track and assign credit to datasets. 相似文献
11.
《Journal of Informetrics》2020,14(2):101019
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. 相似文献
12.
中美图书馆学借用知识的比较观察——基于十年引文的分析 总被引：1，自引：0，他引：1
对中美4种图书馆学拔尖期刊3116篇论文的36998篇样本引文进行了多角度分析,发现中美图书馆学理论均广泛借用其他学科知识,借用学科出现长尾现象。从借用学科领域看,美国较关注生命系统领域,中国关注非生命系统领域;从借用知识形式看,中国重视动态知识,美国则更重视稳定知识;从借用知识年代看,美国重视累计的知识,中国更重视现实知识。据此得出结论：中国图书馆学知识体系更接近于应用学科,美国图书馆学知识体系更接近于生命系统学科;中国图书馆学研究重视吸收新知识,忽略知识积累。我国图书馆学研究应加强基础理论研究,加强对纯科学知识的借用,加强生命系统学科知识的借用,注重知识积累与学术传承。图1。表6。参考文献14。 相似文献
13.
郭璇 《图书馆工作与研究》2011,(2):65-68
评价某一学科领域的科学共同体的信息需求,是图书情报部门的一项重要工作。本文运用引文分析法研究了我国1999-2009年图书馆学专业博士生学位论文所利用的文献,旨在确定该科学共同体引用的出版物的数量、语种构成、文献类型、出版年代及高频引用的中外文期刊,以便为图书情报部门有针对性地满足图书馆学研究人员的信息需求及建立有效用的馆藏提供科学依据。 相似文献
14.
Paul Donner 《Journal of Informetrics》2018,12(1):330-343
A standard procedure in citation analysis is that all papers published in one year are assessed at the same later point in time, implicitly treating all publications as if they were published at the exact same date. This leads to systematic bias in favor of early-months publications and against late-months publications. This contribution analyses the size of this distortion on a large body of publications from all disciplines over citation windows of up to 15 years. It is found that early-month publications enjoy a substantial citation advantage, which arises from citations received in the first three years after publication. While the advantage is stronger for author self-citations as opposed to citations from others, it cannot be eliminated by excluding self-citations. The bias decreases only slowly over longer citation windows due to the continuing influence of the earlier years’ citations. Because of the substantial extent and long persistence of the distortions, it would be useful to remove or control for this bias in research and evaluation studies which use citation data. It is demonstrated that this can be achieved by using the newly introduced concept of month-based citation windows. 相似文献
15.
The study explores the publication trends of scholarly journal articles in two core Library and Information Science (LIS) journals indexed under ScienceDirect Database during the period for the period 2000–2010, and for the “Top 25 Hottest Papers” for 2006–2010. It examines and presents an analysis of 1000 research papers in the area of LIS published in two journals: The International Information & Library Review (IILR) and Library & Information Science Research (LISR). The study examines the content of the journals, including growth of the literature, authorship patterns, geographical distributions of authors, distribution of papers by journal, citation pattern, ranking pattern, length of articles, and most cited authors. Collaboration was calculated using Subramanyam's formula, and Lotka's law was used to identify authors' productivity. The results indicated that authors' distributions did not follow Lotka's law. The study identified the eight most productive authors with a high of 19 publications in this field. The findings indicate that these publications experienced rapid and exponential growth in literature production. The contributions by scientists from India are examined. 相似文献
16.
17.
[目的/意义]在学术交流日趋国际化的背景下,本文拟探索引文国际化与被引量之间的关系,力图回答良好的国际视野是否有助于提升论文的学术影响力这一学界普遍关注的问题。[研究设计/方法]以社会科学为研究对象,选取管理学、图书情报学和新闻传播学的181,406篇CSSCI论文为研究样本,采用相关分析、非参数检验与回归分析的方法研究引用外文期刊论文的数量、学术质量、学科领域、时效性对论文被引量的影响。[结论/发现]在控制了文献类型、期刊声誉等若干可能影响论文被引量的因素后,发现样本论文的引文国际化水平对其被引量具有显著的正向影响。具体而言,引用外文期刊论文的数量越多、平均学术质量越高、学科专属度越高、平均时效性越强的论文具有更高的被引量。[创新/价值]证实了国际视野有助于提升中文社科论文的学术影响力,并提出了有针对性的建议。 相似文献
18.
《Journal of Informetrics》2022,16(1):101235
With the advancement of science and technology, the number of academic papers published each year has increased almost exponentially. While a large number of research papers highlight the prosperity of science and technology, they also give rise to some problems. As we know, academic papers are the most intuitive embodiment of the research results of scholars, which can reflect the level of researchers. It is also the standard for evaluation and decision-making of them, such as promotion and allocation of funds. Therefore, how to measure the quality of an academic paper is very critical. The most common standard for measuring the quality of academic papers is the number of citation counts of them, as this indicator is widely used in the evaluation of scientific publications. It also serves as the basis for many other indicators (such as the h-index). Therefore, it is very important to be able to accurately predict the citation counts of academic papers. To improve the effective of citation counts prediction, we try to solve the citation counts prediction problem from the perspective of information cascade prediction and take advantage of deep learning techniques. Thus, we propose an end-to-end deep learning framework (DeepCCP), consisting of graph structure representation and recurrent neural network modules. DeepCCP directly uses the citation network formed in the early stage of the paper as the input, and outputs the citation counts of the corresponding paper after a period of time. It only exploits the structure and temporal information of the citation network, and does not require other additional information. According to experiments on two real academic citation datasets, DeepCCP is shown superior to the state-of-the-art methods in terms of the accuracy of citation count prediction. 相似文献
19.
《Journal of Informetrics》2020,14(4):101067
Today’s scientific research is an expensive enterprise funded primarily by taxpayers’ and corporate groups’ monies. All nations want to discover fields of study that promise to create future industries, and dominate these by building up and securing scientific and technological expertise early. However, the conversion of scientific leadership into market dominance remains very much an alchemy. To gain insights into how science becomes technology, we focused on graphene (which shows promise in batteries, sensors, flexible displays and other technologies) as a case study. In particular, we asked whether research on the material is on track to deliver all its technological promises. To answer this question, we analyzed in this paper bibliometric records of scientific journal publications and patents related to graphene. While performing straightforward analyses at the aggregate and temporal level to do so, we stumbled upon evidences that suggest ‘Golden Eras’ of graphene science and technology in the recent past. To confirm this unexpected finding, we developed a novel simulation-based method to determine how the interest levels in graphene science and technology change with time. We then found compelling evidences that these interest levels peaked in 2010 and 2012 respectively, despite the continued growth of journal and patent publications in this area. This suggests that publication numbers in a research topic could sometimes give rise to false positives concerning its importance. 相似文献
20.
首先对我国图书馆学方法论研究作了简单的评述,然后分析引文分析法在进入21世纪以后在图书馆学研究中所起到的重要作用以及这种方法对图书馆学研究所具有的独特作用,由此认为引文分析法是图书馆学研究的一种十分重要的、名副其实的专门方法,并提出必须进一步研究引文分析法。 相似文献