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1.
[目的/意义] 科研评价中,短时间引文窗口下的学科标准化指标往往是不可靠的,因为这时论文发表的时间较短,还没有充足的时间获取被引次数。然而,各种标准化方法本身并不能解决这一问题。研究旨在解决这一科研评价中的难题。[方法/过程] 研究引入一个权重因素以表示每篇论文标准分的可靠程度,权重由论文在给定的短时间窗口下的被引次数与长时间窗口下被引次数的相关系数计算获得,论文发表时间越短(长),可靠性越低(高),权重也越低(高)。为验证加权效果,将权重与常用的学科标准化指标CNCI进行加权处理,计算世界500强大学每所大学所有论文加权后的总影响力TWCNCI值与未加权时的总影响力TCNCI值。[结果/结论] 研究发现,500强大学的TWCNCI值与TCNCI值,TWCNCI的排名与TCNCI的排名都具有极强的相关性,但是仍有部分大学在加权后排名发生明显波动。据此,研究认为标准化指标在短时间窗口下不可靠的弊端以及对此修正的权重因素在科研评价中不应忽视。  相似文献   

2.
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   

3.
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to the citation network setting, and show that there are authors who frequently cite recent papers that become highly-cited in the future; these authors are referred to as discoverers. We develop a method for early identification of highly-cited papers based on the early citations from discoverers. The results show that the identified discoverers have a consistent citing pattern over time, and the early citations from them can be used as a valuable indicator to predict the future citation counts of a paper. The discoverers themselves are potential future outstanding researchers as they receive more citations than average.  相似文献   

4.
[目的/意义]分析学科规范引文影响力在科学评价中的可行性及其与同行评议的相关性,为负责任计量及以其为支撑的同行评议提供借鉴。[方法/过程]选取F1000以及InCites平台,将29 850篇细胞生物学文献、30 326篇生物技术文献的CNCI （学科规范化引文影响力）与被引频次进行相关分析,对其中956篇细胞生物学论文的CNCI与F1000分值进行斯皮尔曼相关系数检验。[结果/结论]研究结果表明,从统计学视角看CNCI与被引频次呈高度正相关,与F1000分值呈显著正相关,同时亦存在二者相悖的情形。因此,CNCI在一定程度上能够反映同行评议结果、能代偿实施学术影响力归誉的功能,并适用于跨学科比较;但同行评议或CNCI单独作为科学评价标准都会有失偏颇,以CNCI为代表的新一代负责任计量指标为支撑的同行评议将成为未来科学评价的主流。  相似文献   

5.
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   

6.
Journal metrics are employed for the assessment of scientific scholar journals from a general bibliometric perspective. In this context, the Thomson Reuters journal impact factors (JIFs) are the citation-based indicators most used. The 2-year journal impact factor (2-JIF) counts citations to one and two year old articles, while the 5-year journal impact factor (5-JIF) counts citations from one to five year old articles. Nevertheless, these indicators are not comparable among fields of science for two reasons: (i) each field has a different impact maturity time, and (ii) because of systematic differences in publication and citation behavior across disciplines. In fact, the 5-JIF firstly appeared in the Journal Citation Reports (JCR) in 2007 with the purpose of making more comparable impacts in fields in which impact matures slowly. However, there is not an optimal fixed impact maturity time valid for all the fields. In some of them two years provides a good performance whereas in others three or more years are necessary. Therefore, there is a problem when comparing a journal from a field in which impact matures slowly with a journal from a field in which impact matures rapidly. In this work, we propose the 2-year maximum journal impact factor (2M-JIF), a new impact indicator that considers the 2-year rolling citation time window of maximum impact instead of the previous 2-year time window. Finally, an empirical application comparing 2-JIF, 5-JIF, and 2M-JIF shows that the maximum rolling target window reduces the between-group variance with respect to the within-group variance in a random sample of about six hundred journals from eight different fields.  相似文献   

7.
The purpose of the Kazakh publication citation indicator that has been developed in Kazakhstan since 2005 is to carry out scientometric analysis of scientific publications to determine their citation rate. At present, the bibliographic database (BDB) on citation includes information on the publication activities and citation index of approximately 30000 Kazakh scientists and specialists. They had over 18000 scientific papers published in over 500 domestic and foreign journals. The total quantity of references to papers by Kazakh scientists was more than 28000. The Kazakh analogue of the science citation index determination system is an efficient tool for analytical work with the BDB of scientific publications, which makes it possible to calculate publication activities and citation parameters, which are used to define the value and demand for the results of scientific work in various fields of domestic science.  相似文献   

8.
The journal impact factor is not comparable among fields of science and social science because of systematic differences in publication and citation behavior across disciplines. In this work, a source normalization of the journal impact factor is proposed. We use the aggregate impact factor of the citing journals as a measure of the citation potential in the journal topic, and we employ this citation potential in the normalization of the journal impact factor to make it comparable between scientific fields. An empirical application comparing some impact indicators with our topic normalized impact factor in a set of 224 journals from four different fields shows that our normalization, using the citation potential in the journal topic, reduces the between-group variance with respect to the within-group variance in a higher proportion than the rest of indicators analyzed. The effect of journal self-citations over the normalization process is also studied.  相似文献   

9.
Main path analysis is a popular method for extracting the backbone of scientific evolution from a (paper) citation network. The first and core step of main path analysis, called search path counting, is to weight citation arcs by the number of scientific influence paths from old to new papers. Search path counting shows high potential in scientific impact evaluation due to its semantic similarity to the meaning of scientific impact indicator, i.e. how many papers are influenced to what extent. In addition, the algorithmic idea of search path counting also resembles many known indirect citation impact indicators. Inspired by the above observations, this paper presents the FSPC (Forward Search Path Count) framework as an alternative scientific impact indicator based on indirect citations. Two critical assumptions are made to ensure the effectiveness of FSPC. First, knowledge decay is introduced to weight scientific influence paths in decreasing order of length. Second, path capping is introduced to mimic human literature search and citing behavior. By experiments on two well-studied datasets against two carefully created gold standard sets of papers, we have demonstrated that FSPC is able to achieve surprisingly good performance in not only recognizing high-impact papers but also identifying undercited papers.  相似文献   

10.
The findings of Bornmann, Leydesdorff, and Wang (2013b) revealed that the consideration of journal impact improves the prediction of long-term citation impact. This paper further explores the possibility of improving citation impact measurements on the base of a short citation window by the consideration of journal impact and other variables, such as the number of authors, the number of cited references, and the number of pages. The dataset contains 475,391 journal papers published in 1980 and indexed in Web of Science (WoS, Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these papers. As an indicator of citation impact, we used percentiles of citations calculated using the approach of Hazen (1914). Our results show that citation impact measurement can really be improved: If factors generally influencing citation impact are considered in the statistical analysis, the explained variance in the long-term citation impact can be much increased. However, this increase is only visible when using the years shortly after publication but not when using later years.  相似文献   

11.
苏芳荔 《图书情报工作》2011,55(10):144-148
以图情类影响力最大的4种期刊在2000-2009年的载文量与被引频次为样本,采用符号检验与相关分析的方法,从合作模式与合作频率两个方面分析科研合作对期刊论文被引频次的影响。研究发现：①合作发表论文的影响力明显高于独立（无合作）发表的论文;②在获得被引频次方面,国际合作并不优于国内合作,高校并不优于研究所;③研究机构的合作次数与被引频次呈正线性相关关系,但机构的合作频率与篇均被引次数没有显著相关。  相似文献   

12.
[目的/意义] 探讨不同学科分类体系在机构科研影响力评价中的差异及对评价结果的影响。[方法/过程] 以Incites数据库为数据来源,选择5种分类体系、8种分类方案。首先对14 955个机构不同分类方案下的学科标准化引文影响力(Category Normalized Citation Impact,CNCI)进行相关性分析,考察不同分类体系下评价结果的整体相似性。然后以国内双一流建设中的36所高校为例,比较和分析不同分类方案下机构CNCI值的变化情况及差异产生的具体原因,研究分类体系对个体机构评价的影响。[结果/结论] 不同学科分类方案下得到的CNCI值相关性显著(最低相关性达到0.85),即不同分类体系得到的整体评价结果具有较高的相似度。但是不同分类体系下的评价结果也存在聚类特征,OECD、ESI、SCADC、CT1相互之间相关系数高、结果更相近,WoS、CT2和CT3评价结果更接近,分类体系的粒度是决定评价结果的重要因素。36所高校在不同的分类体系下评价结果的整体相关性较高,但个别高校CNCI值变化较大,特别是在热点主题上有突出发文的机构。评价结果的巨大差异其根本原因是论文划分到不同类目中,不同类目下的引用基准值不同。在评价过程中更加推荐粒度较细的分类体系,减少热点主题等对引用基准值的影响。  相似文献   

13.
In an age of intensifying scientific collaboration, the counting of papers by multiple authors has become an important methodological issue in scientometric based research evaluation. Especially, how counting methods influence institutional level research evaluation has not been studied in existing literatures. In this study, we selected the top 300 universities in physics in the 2011 HEEACT Ranking as our study subjects. We compared the university rankings generated from four different counting methods (i.e. whole counting, straight counting using first author, straight counting using corresponding author, and fractional counting) to show how paper counts and citation counts and the subsequent university ranks were affected by counting method selection. The counting was based on the 1988–2008 physics papers records indexed in ISI WoS. We also observed how paper and citation counts were inflated by whole counting. The results show that counting methods affected the universities in the middle range more than those in the upper or lower ranges. Citation counts were also more affected than paper counts. The correlation between the rankings generated from whole counting and those from the other methods were low or negative in the middle ranges. Based on the findings, this study concluded that straight counting and fractional counting were better choices for paper count and citation count in the institutional level research evaluation.  相似文献   

14.
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   

15.
[目的/意义]探索中文学术期刊论文的引文模式及时间窗口的选择对引文模式的影响，建立引文模式的分析框架。[方法/过程]以2006-2008年出版的图书情报领域期刊论文作为研究对象，采用两步聚类法对单篇论文在7年内的绝对被引量与相对被引量进行聚类分析，研究论文主要特征因子与引文模式的相关性。[结果/结论]在绝对被引量视角下，期刊论文均表现为先上升后下降的经典引文模式；在相对下载量视角下，期刊论文共有6种引文模式，其中3种可以归纳为经典引文模式，另外3种分别为"类睡美人型"、正偏型和马拉松型。相对被引量视角下，首年被引量与总被引量呈现了中等甚至较强的相关性，并且平均被引量越高，相关性越强，绝对被引量视角下的结果正好相反。结果表明，期刊论文的初始被引量与总被引量的相关性高低主要取决于引文曲线的峰度而非总被引量的大小。  相似文献   

16.
[目的/意义]探讨被引频次位置指标在科技期刊评价中的作用,确定合适时间窗口的最优位置指标。[方法/过程]从Web of Science数据库中选取符合条件的14种眼科期刊作为研究对象,分别计算各期刊2014年度不同位置指标,包括2年、5年、8年和10年引证时间窗口(citation time window,CTW)的h指数(h2、h5、h8和h10)、累计h指数(a-h2、a-h5、a-h8和a-h10)以及相对应的期刊2014年度被引频次百分位数位置(percentage rank position,PRP)指标(Top1%、Top5%、Top10%、Top25%Top50%)和累计PRP指标(a-Top1%、a-Top5%、a-Top10%、a-Top25%和a-Top50%)。比较影响因子、不同CTW位置指标与期刊问卷调查评分的相关度,确定不同位置指标应用于期刊评价的效果。[结果/结论]合理的位置指标在期刊影响力评价中优于影响因子和5年影响因子,累计被引频次位置指标普遍优于年度指标,2年CTW的h指数优于其他CTW的h指数,5年CTW的a-h2、h2,5年和8年CTW的a-Top50%和Top50%与影响因子和5年影响因子相比具有更理想的期刊评价效果。  相似文献   

17.
Bibliometricians have long recurred to citation counts to measure the impact of publications on the advancement of science. However, since the earliest days of the field, some scholars have questioned whether all citations should be worth the same, and have gone on to weight them by a variety of factors. However sophisticated the operationalization of the measures, the methodologies used in weighting citations still present limits in their underlying assumptions. This work takes an alternative approach to resolving the underlying problem: the proposal is to value citations by the impact of the citing articles, regardless of the length of their reference list. As well as conceptualizing a new indicator of impact, the work illustrates its application to the 2004–2012 Italian scientific production indexed in the WoS. The proposed impact indicator is highly correlated to the traditional citation count, however the shifts observed between the two measures are frequent and the number of outliers not negligible. Moreover, the new indicator shows greater “sensitivity” when used to identify the highly-cited papers.  相似文献   

18.
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   

19.
Citation behaviour is the source driver of scientific dynamics, and it is essential to understand its effect on knowledge diffusion and intellectual structure. This study explores the effect of citation behaviour on disciplinary knowledge diffusion and intellectual structure by comparing three types of citation behaviour trends, namely the high citation trend, medium citation trend, and low citation trend. The diffusion power, diffusion speed, and diffusion breadth were calculated to quantify knowledge diffusion. The properties of the global and local citation network structure were used to reflect the particular influences of citation behaviour on the scientific intellectual structure. The primary empirical results show that (a) the high citation behaviour trend could improve the knowledge diffusion speed for papers with a short citation history span. Additionally, the medium citation trend has the broadest diffusion breadth whereas the low citation behaviour trend might make the citation counts take off for papers with a long citation history span; (b) the high citation trend has a stronger influence and greater control over the intellectual structure, but this relationship is true only for papers with a short or normal citation history span. These findings could play important roles in scientific research evaluation and impact prediction.  相似文献   

20.
如何提高英文版科技期刊的被引频次和影响因子   总被引：3，自引：0，他引：3  
蔡斐 《编辑学报》2005,17(2):133-134
从总被引频次和影响因子2方面分析我国英文版科技期刊的引用指标的现状和引用指标偏低的原因.提出了提高英文版科技期刊被引频次和影响因子的措施:1)注重期刊的国内外发行工作;2)通过建立英文网站及加入国内外知名数据库,提高文章的点击率及浏览量;3)请专家把语言关.  相似文献   

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