共查询到16条相似文献，搜索用时 203 毫秒
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篇均来源期刊标准影响(SNIP)为荷兰学者Moed教授于2010年提出的全新期刊评价指标,旨在对不同主题领域的期刊影响力进行评价,为验证这一评价指标在期刊评价实践中的效用,利用SPSS18.0数据统计分析软件对Scopus数据库中24种外文期刊的SNIP与SJR、h指数以及影响因子进行实证对比分析;以CSSCI为来源数据库统计分析国内6种图书情报学期刊的IF值与SNIP值。分析结果证明,SNIP与其他3个指标之间存在较强的相关性,在期刊评价实践中具有可行性。 相似文献
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Scopus数据库引文评价新指标SNIP原理及可行性探讨 总被引：1，自引：0，他引：1
介绍期刊评价新指标SNIP的基本原理和计算方法,通过与IF的对比,分析其优势和不足,初步验证它的可行性,并针对SNIP在我国期刊评价中的应用提出建议,以为我国期刊评价指标研究提供参考。 相似文献
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针对Z指数不能实现跨学科领域期刊评价的缺陷,文章通过引入学科规范化引文影响力修正不同学科的引用差异,改进Z指数并提出ZCNCI指数。通过分析ZCNCI指数与Z指数、P指数、SNIP、标准化特征因子、影响因子百分位等指标的相关性和差异性,验证ZCNCI指数跨学科期刊评价的效力。结果表明,ZCNCI指数延续了Z指数综合反映期刊数量、质量和被引分布特征的优势,与Z指数、P指数、标准化特征因子的相关性较高,且克服了SNIP、影响因子百分位的评价缺陷,在跨学科期刊评价中的综合表现较好。ZCNCI指数具有跨学科期刊评价效力,可用于跨学科期刊评价。 相似文献
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期刊评价指标实证研究 总被引：1，自引：0，他引：1
本文选取F1000数据库中免疫学与生物信息学论文近2000篇,通过相关分析、聚类分析以及因子分析将对应260种期刊的影响因子、5年期影响因子、特征因子、论文影响分值、即时指数、SJR、SNIP、期刊h-指数进行相关性检验及分类,并对各项指标与同行评议结果即F1000因子进行相似性比较.结果表明各项指标虽源于WoS和Scopus不同数据库,计算方法也不尽相同,但其间具有较好的一致性,从而为WoS与Scopus在科学评价中的可选择性与替代性提供依据.本文论述中结合期刊评价进化历程,并通过各项指标优缺点的剖析,指出期刊评价的发展趋向. 相似文献
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文章讨论了四个近年来新提出的科研评价指标,即修正的源标准化论文影响力指数(the Revised Source Normalized Impact per Paper,Revised SNIP),相对度量指数(Relative Measurement Index,RMI),标准化影响因子(Normalized Impact Factor,NIF)和c指数(c-index),分别论述了各个指标的定义、优势和缺点.
修正的SNIP指数.SNIP指数是Moed于2010年提出的,已经在Elsevier的Scopus库中得到应用.它的定义是SNIP=RIP/RDCP,其中RIP(Raw Impact per Paper)是论文原始影响力,用三年期影响因子来表示,RDCP(Relative Database Citation Potential,RDCP)是相对数据库引用潜力值,定义为期刊的DCP值与该数据库的DCP中位数值的比率: 相似文献
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文章以2016JCR中SSCI收录信息科学与图书馆学学科期刊为来源数据,采用Spearman分析2年影响因子百分位、5年影响因子百分位和他引影响因子百分位与WoS数据库其他文献计量学指标、与h指数及累积h指数、与Scopus数据指标的相关度的不同.5年影响因子百分位与WoS数据库计量指标总被引频次、5年影响因子、被引半衰期、论文影响分值、引用半衰期、特征因子和标准特征因子的相关度高于2年影响因子百分位和他引影响因子百分位;5年影响因子百分位与相同引证时间窗口h指数、累积h指数全部表现为最强相关性,与Scopus数据库计量指标CiteScore、SNIP和SJR均表现显著相关性.5年影响因子百分位对期刊的评价效力更高,更适用于期刊的学术评价. 相似文献
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通过对比F1000因子与被引频次、F1000因子与期刊评价指标,并对主要指标进行相关性分析,来验证同行评议与引文分析间的相关性。结果表明,F1000因子与被引频次呈正相关性,即专家打分与被引频次变动方向相同;但也存在专家打分高的论文被引频次低,而专家打分低的论文被引频次高的事实。相关性分析的结果表明：在特征因子、SNIP等主要指标中,SJR、IF与专家评议值相关度最大。 相似文献
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随着政府对科技投入的增加,科研评价已然成为科技战略管理的重要工具。在微观层面,对研究人员的评价,目前许多研究机构不仅仅关注论文数,也关注论文发表期刊的质量。在实际操作中,从时间和经济条件考虑,大样本的学术期刊评价常常要参照定量指标,如期刊的h指标。虽然该指标学术意义重大,但本研究指出h指标本质问题之一在于：h核选取标准的局部性使得应用它进行期刊分类或排名时缺乏可比性,导致基于h指标的期刊评价方法有理论上的缺陷。针对该问题,本研究提出构造全局性的期刊h指标（Gh指标和Ghadj指标）,并在实例研究的基础上提出基于Ghadj指标的期刊影响力等级划分新方法,即Lj分类法。通过案例研究与其他期刊评价结果相比,发现Lj期刊分类结果与英国运筹学协会的专家意见更为接近,且更具有实际操作意义。该研究可为科技管理提供学术期刊评价的新思路。 相似文献
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现有的学术期刊评价缺乏同时对期刊影响力与期刊知识扩散能力的评价,为此本文构建了学术期刊影响深度与影响宽度的评价框架,并提出期刊综合影响指数的概念:采用被引频次、影响因子、h指数评价期刊影响深度,采用扩散因子、新扩散因子评价期刊影响宽度,通过期刊影响宽度与影响深度计算期刊综合影响因子。利用中国知网引文数据库(CNKI)的引文数据,对图书馆情报与文献学CSSCI期刊的研究表明:期刊影响深度、期刊影响宽度、期刊综合影响指数均服从正态分布,统计指标特征相近;期刊综合影响指数与评价指标正相关,说明该指标评价是稳健的;期刊综合影响指数与自引率、载文量无关,可以防止指标人为操纵。表5。参考文献18。 相似文献
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A new size-independent indicator of scientific journal prestige, the SJR2 indicator, is proposed. This indicator takes into account not only the prestige of the citing scientific journal but also its closeness to the cited journal using the cosine of the angle between the vectors of the two journals’ cocitation profiles. To eliminate the size effect, the accumulated prestige is divided by the fraction of the journal's citable documents, thus eliminating the decreasing tendency of this type of indicator and giving meaning to the scores. Its method of computation is described, and the results of its implementation on the Scopus 2008 dataset is compared with those of an ad hoc Journal Impact Factor, JIF(3y), and SNIP, the comparison being made both overall and within specific scientific areas. All three, the SJR2 indicator, the SNIP indicator and the JIF distributions, were found to fit well to a logarithmic law. Although the three metrics were strongly correlated, there were major changes in rank. In addition, the SJR2 was distributed more equalized than the JIF by Subject Area and almost as equalized as the SNIP, and better than both at the lower level of Specific Subject Areas. The incorporation of the cosine increased the values of the flows of prestige between thematically close journals. 相似文献
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Ludo Waltman Nees Jan van Eck Thed N. van Leeuwen Martijn S. Visser 《Journal of Informetrics》2013,7(2):272-285
The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined.In this paper, a number of modifications that were recently made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well. 相似文献
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期刊引用认同及其被引评价新指标有效性分析 总被引：2，自引：1，他引：1
以影响因子等引文数据为核心的期刊评价指标体系虽广为使用,但也备受争议.本文从期刊引用认同、期刊被引及期刊国际化等三个方面分析了不仅仅依赖于"影响因子"的评价期刊的新指标,并对相关指标的有效性问题进行讨论.分析表明,基于期刊引用认同视角和基于期刊被引网络视角的很多指标可以与期刊影响因子指标相印证,可用作国内期刊评价的新尝试,而相关期刊国际化评价指标还需在实践中进一步检验. 相似文献
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《Journal of Informetrics》2014,8(4):985-996
We study the correlation between citation-based and expert-based assessments of journals and series, which we collectively refer to as sources. The source normalized impact per paper (SNIP), the Scimago Journal Rank 2 (SJR2) and the raw impact per paper (RIP) indicators are used to assess sources based on their citations, while the Norwegian model is used to obtain expert-based source assessments. We first analyze – within different subject area categories and across such categories – the degree to which RIP, SNIP and SJR2 values correlate with the quality levels in the Norwegian model. We find that sources at higher quality levels on average have substantially higher RIP, SNIP, and SJR2 values. Regarding subject area categories, SNIP seems to perform substantially better than SJR2 from the field normalization point of view. We then compare the ability of RIP, SNIP and SJR2 to predict whether a source is classified at the highest quality level in the Norwegian model or not. SNIP and SJR2 turn out to give more accurate predictions than RIP, which provides evidence that normalizing for differences in citation practices between scientific fields indeed improves the accuracy of citation indicators. 相似文献