A stochastic approach to the relation between the impact factor and the uncitedness factor

Empirical analysis of the relationship between the impact factor – as measured by the average number of citations – and the proportion of uncited material in a collection dates back at least to van Leeuwen and Moed (2005) where graphical presentations revealed striking patterns. Recently Hsu and Huang (2012) have proposed a simple functional relationship. Here it is shown that the general features of these observed regularities are predicted by a well-established informetric model which enables us to derive a theoretical van Leeuwen–Moed lower bound. We also question some of the arguments of Hsu and Huang (2012) and Egghe (2013) while various issues raised by Egghe, 2008, Egghe, 2013 are also addressed.     

高校学报影响因子与其所属高校综合实力的相关性

根据武书连"2012中国大学综合实力排行榜"和2012年版《中国科技期刊引证报告》的数据,对综合实力排名前10位的高校(排名)和其学报影响因子按学科分别进行了统计学相关性分析,同时对全国自然科学、人文社科类高校学报影响因子与其所属高校的排名进行了统计学相关性分析。结果表明,在一定条件下高校学报的影响因子与其高校排名存在一定相关性,但总体而言,相关性不强。     

论知识经济与编辑出版产业的互动发展

在指出编辑出版业是当前知识经济研究中被忽视的产业之后,从构成知识经济的三要素是知识创新、知识传播、知识应用的角度,论述了编辑出版业是知识经济链条上的重要环节,并从编辑出版业的存储、导向、优化和组织等社会功能的角度,论述了编辑出版业是推动知识经济发展的原动力;又从社会发展趋势和行业性质两个方面论述了知识经济是编辑出版业继续发展的前提,指出知识经济时代为编辑出版业的继续发展提供了良好的条件和机遇,从而得出知识经济与编辑出版产业互动发展的结论。     

Publication delay adjusted impact factor: The effect of publication delay of articles on journal impact factor

The journal impact factor (JIF) has been questioned considerably during its development in the past half-century because of its inconsistency with scholarly reputation evaluations of scientific journals. This paper proposes a publication delay adjusted impact factor (PDAIF) which takes publication delay into consideration to reduce the negative effect on the quality of the impact factor determination. Based on citation data collected from Journal Citation Reports and publication delay data extracted from the journals’ official websites, the PDAIFs for journals from business-related disciplines are calculated. The results show that PDAIF values are, on average, more than 50% higher than JIF results. Furthermore, journal ranking based on PDAIF shows very high consistency with reputation-based journal rankings. Moreover, based on a case study of journals published by ELSEVIER and INFORMS, we find that PDAIF will bring a greater impact factor increase for journals with longer publication delay because of reducing that negative influence. Finally, insightful and practical suggestions to shorten the publication delay are provided.     

The impact of functional decentralization and externalization on local government transparency

Local governments are increasingly establishing functional decentralized agencies, such as autonomous organizations, public companies, foundations and public business entities to provide public services. Furthermore, they are also introducing the private sector, contracting out public services to a private company and creating mixed companies. Our aim is to analyze the effect of functional decentralization and externalization (outsourcing or contracting out) processes on public transparency levels, since theoretically, they are aimed toward good governance and accountability. To do so, we use a sample composed of the 110 largest Spanish cities for the period 2008–2010. The results show that decentralized agencies, especially public companies and foundations, impact positively on levels of public transparency. However, there is no evidence that suggests that the introduction of the private sector, using outsourcing and mixed companies, affects the transparency of local governments.     

Relationship between an editor in chief's commentary publications and the impact factor of cardiovascular medicine journals

Journal impact factor (IF) inflation is suggested as a problem resulting from commentaries published by the editors in chief (EiCs) of their respective journals. However, it is unclear whether this is a systemic problem across the top thirty cardiovascular medicine journals. Therefore, the purpose of this investigation was to examine the relationship between the number of commentaries written by an EiC and their journal''s IF and Eigenfactor (Ef). Utilizing Spearman rank partial correlations controlling for length of service as the EiC, significant moderate correlations were found between the number of commentaries and the number of first-author commentaries by the EiC and the IF of their journal (r=0.568, p=0.001 and r=0.504, p=0.005; respectively). A weak but still significant correlation was found between the number of commentaries by the EiC and the Ef of their journal (r=0.431, p=0.020). The reason for these correlations is unclear, and whether the methodology used to compute the IF and Ef should be modified needs further research.     

期刊影响因子操纵行为及抑制策略

国内外一些学术期刊利用期刊影响因子定义与计算方法存在的漏洞,采取多种操纵行为拉高影响因子。由于期刊影响因子被广泛应用于学术评价与科研管理,不客观期刊影响因子对学术评价与科研管理造成不能忽略的较大负面影响。本文总结了过度自引、同盟引用、引用奖金等代表性期刊影响因子操纵行为,并提出抑制策略。     

Mathematical derivation of the impact factor distribution

Experimental data [Mansilla, R., Köppen, E., Cocho, G., & Miramontes, P. (2007). On the behavior of journal impact factor rank-order distribution. Journal of Informetrics, 1(2), 155–160] reveal that, if one ranks a set of journals (e.g. in a field) in decreasing order of their impact factors, the rank distribution of the logarithm of these impact factors has a typical S-shape: first a convex decrease, followed by a concave decrease. In this paper we give a mathematical formula for this distribution and explain the S-shape. Also the experimentally found smaller convex part and larger concave part is explained. If one studies the rank distribution of the impact factors themselves, we now prove that we have the same S-shape but with inflection point in μ, the average of the impact factors. These distributions are valid for any type of impact factor (any publication period and any citation period). They are even valid for any sample average rank distribution.     

Empirical modeling of the impact factor distribution

The distribution of impact factors has been modeled in the recent informetric literature using two-exponent law proposed by Mansilla, Köppen, Cocho, and Miramontes (2007). This paper shows that two distributions widely-used in economics, namely the Dagum and Singh-Maddala models, possess several advantages over the two-exponent model. Compared to the latter, the former models give as good as or slightly better fit to data on impact factors in eight important scientific fields. In contrast to the two-exponent model, both proposed distributions have closed-from probability density functions and cumulative distribution functions, which facilitates fitting these distributions to data and deriving their statistical properties.     

The significance of an impact factor: implications for the publishing community

The journal impact factor, as a metric developed in the mid‐1960s by Dr Eugene Garfield and Dr Irving Sher, represents the influence that an ‘average article’ published in a specific journal has on the scholarly discipline and audience that it serves. Originally intended to serve as an equalizer for use by the Institute for Scientific Information® (ISI®) in making comparative evaluations of large and small journals in a particular discipline, the impact factor now has numerous applications for publishers, librarians, and researchers. Ideally, the journal impact factor should be seen by publishers as a useful tool in gauging the effectiveness of their publication product in serving the needs of a particular scholarly community. The significance of a journal impact factor, its appropriate usage by the scholarly publishing community and its extension into the electronic environment are discussed.     

虚拟参考咨询服务与图书馆知识管理的契合关系

通过解读图书馆虚拟参考咨询服务并对图书馆知识管理的涵义与内容进行分析,文章认为虚拟参考咨询服务与图书馆知识管理在客观上存在着诸多契合面,二者均可为对方带来新的思路与发展转机。提出将知识管理理念导入图书馆虚拟参考咨询服务,把虚拟参考咨询服务作为图书馆知识管理实施的切入点的观点并进行论证。     

Video tutorials revisited: The relationship between their use and library assessment quiz scores

There is considerable literature evaluating video tutorials. By the first decade of the twenty-first century, research established that online video tutorials performed as well as traditional face-to-face instruction. However, there is little evidence that students actually viewed the tutorials. This study compares postinstruction assessment quiz scores from one class over four semesters with usage statistics for five video tutorials during the same time frame. The data indicate that students do view the tutorials. However, the results also show that usage statistics, together with quiz scores, declined as students progressed through the five tutorials. Additionally, the study determined that there was no positive correlation between the number of viewings and postviewing assessment scores.     

论期刊影响因子人为操纵的识别

近年来,期刊影响因子的人为操纵受到学术界广泛关注,期刊过度自引成为人为操纵影响因子的重要手段.期刊自引率是识别影响因子人为操纵的敏感指标,但对小集团内部期刊互引和其他形式人为操纵的识别却无能为力.在该研究中,深度挖掘了自引率、扩散因子、被引半衰期、开放因子和互引指数在期刊影响因子人为操纵识别中的应用.     

Journal topic citation potential and between-field comparisons: The topic normalized impact factor

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.     

影响因子的应用现状及展望

影响因子IF作为重要的文献计量学工具,对于评价期刊学术质量,提供选刊参考,评判科研产出具有一定的作用;但是,IF自身的局限性,要求必须明确其应用范围,同时应根据实际评价目标和对象选择相适应的评判标准和指标体系.     

On the behavior of journal impact factor rank-order distribution

An empirical law for the rank-order behavior of journal impact factors is found. Using an extensive data base on impact factors including journals on education, agrosciences, geosciences, mathematics, chemistry, medicine, engineering, physics, biosciences and environmental, computer and material sciences, we have found extremely good fittings outperforming other rank-order models. Based in our results, we propose a two-exponent Lotkaian Informetrics. Some extensions to other areas of knowledge are discussed.     

Estimating the accuracies of journal impact factor through bootstrap

The journal impact factor (JIF) reported in journal citation reports has been used to represent the influence and prestige of a journal. Whereas the consideration of the stochastic nature of a statistic is a prerequisite for statistical inference, the estimation of JIF uncertainty is necessary yet unavailable for comparing the impact among journals. Using journals in the Database of Research in Science Education (DoRISE), the current study proposes bootstrap methods to estimate the JIF variability. The paper also provides a comprehensive exposition of the sources of JIF variability. The collections of articles in the year of interest and in the preceding years both contribute to JIF variability. In addition, the variability estimate differs depending on the way a database selects its journals for inclusion. In the bootstrap process, the nested structure of articles in a journal was accounted for to ensure that each bootstrap replication reflects the actual citation characteristics of articles in the journal. In conclusion, the proposed point and interval estimates of the JIF statistic are obtained and more informative inferences on the impact of journals can be drawn.     

科技期刊影响力数据稳定性的数学描述

参照统计学中的置信限的概念,定义了影响力数据的置信限和稳定度。这一定义不仅综合考虑了影响因子、特征因子、总被引频次、载文量等文献计量指标,而且具有计算简便、可操作性较强的特点。通过对工程技术类79种期刊的实例计算与分析,进一步论证了有关影响因子的置信限与稳定度在研究评价和期刊评估中的实用性。