Impact maturity times and citation time windows: The 2-year maximum journal impact factor

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.     

Some comments on the journal weighted impact factor proposed by Habibzadeh and Yadollahie

In a recent paper in the Journal of Informetrics, Habibzadeh and Yadollahie [Habibzadeh, F., & Yadollahie, M. (2008). Journal weighted impact factor: A proposal. Journal of Informetrics, 2(2), 164–172] propose a journal weighted impact factor (WIF). Unlike the ordinary impact factor, the WIF of a journal takes into account the prestige or the influence of citing journals. In this communication, we show that the way in which Habibzadeh and Yadollahie calculate the WIF of a journal has some serious problems. Due to these problems, a ranking of journals based on WIF can be misleading. We also indicate how the problems can be solved by changing the way in which the WIF of a journal is calculated.     

The use of a weighted impact factor for the creation of a polythematic list of the most cited journals

The standard impact factor allows one to compare scientific journals only within particular scientific subjects. To overcome this limitation, another indicator of citation, viz., the thematically weighted impact factor (TWIF), is proposed. This indicator allows one to compare journals of various subjects and takes the fact that a journal belongs to several subjects into account. Information on the thematic headings of a journal and the value of a standard impact factor is necessary for calculation of the indicator. The TWIF, which is calculated according to the citation index of Journal Citation Reports, is investigated in this article.     

On the skewness of journal self‐citations and publisher self‐citations: Cues for discussion from a case study

This paper takes the cue from the case of a retracted paper, cited both by the retraction notice and by an article published later in the same journal. This led to analysis and discussion on the skewness of citations in the journal Sustainability and within Multidisciplinary Digital Publishing Institute (MDPI) journals, particularly investigating self‐citations at journal and publisher levels. I analysed articles published by Sustainability in 2015 and found that self‐citations are higher than expected under a uniform probability distribution. Self‐citations in this journal make a 36% difference to the journal's impact factor. This research raises the question of what citation patterns can be expected as normal, and where the boundary between normal and anomaly lies. I suggest the issue deserves further investigation because self‐citations have several implications, ranging from impact factors to visibility and influence of scientific journals.     

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.     

开放存取对期刊影响力绩效研究综述

文章归纳了国内外主要的OA绩效研究方法,并将它们分为三类：对某个期刊群中OA期刊和非OA期刊影响因子的比较、对某个领域大样本OA论文与非OA论文被引频次的统计比较,以及对某个混合OA期刊中OA论文和非OA论文影响因子平均值的比较,并介绍了其中五个代表性研究的方法和结论。这些研究成果表明,OA对提高期刊影响力有着积极的立竿见影的作用。针对未来需要,文章提出了OA论文比例演变、文献引文中OA文献比例演变、搜索引擎对OA绩效影响的研究方案。该文为《数字图书馆论坛》2．009年第11期本期话题“Open Access”的文章之一。     

Efficiency analysis of forestry journals: Suggestions for improving journals’ quality

In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score.     

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。     

Measuring contextual citation impact of scientific journals

This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject field, especially the frequency at which authors cite other papers in their reference lists, the rapidity of maturing of citation impact, and the extent to which a database used for the assessment covers the field's literature. It further develops Eugene Garfield's notions of a field's ‘citation potential’ defined as the average length of references lists in a field and determining the probability of being cited, and the need in fair performance assessments to correct for differences between subject fields. A journal's subject field is defined as the set of papers citing that journal. SNIP is defined as the ratio of the journal's citation count per paper and the citation potential in its subject field. It aims to allow direct comparison of sources in different subject fields. Citation potential is shown to vary not only between journal subject categories – groupings of journals sharing a research field – or disciplines (e.g., journals in mathematics, engineering and social sciences tend to have lower values than titles in life sciences), but also between journals within the same subject category. For instance, basic journals tend to show higher citation potentials than applied or clinical journals, and journals covering emerging topics higher than periodicals in classical subjects or more general journals. SNIP corrects for such differences. Its strengths and limitations are critically discussed, and suggestions are made for further research. All empirical results are derived from Elsevier's Scopus.     

Update on Journal Impact Ratings in Communication: 2006–2008

Bibliometric data indexed through the Institute for Scientific Information were analyzed for 45 communication journals. Several measures were included to identify the most widely cited journals in the field, including (a) journal impact factor, (b) five-year journal impact, (c) article influence, and (d) journal relatedness. Results serve to expand on findings by Feeley (2008 Feeley , T. H. ( 2008 ). A bibliometric analysis of communication journals from 2002 to 2005 . Human Communication Research , 34 , 505 – 520 .[Crossref], [Web of Science ®] , [Google Scholar]) with respect to overall and within-field influence of communication journals whose analysis covered 2002 through 2005 and 19 journals. Results indicate stability in journal impact ratings over time and several journals (e.g., Communication Research, Human Communication Research, Journal of Communication, Communication Monographs, and Communication Theory) are highly central in the communication journal citation network.     

基于被引频次对数矫正的影响因子及其学科标准化研究

本文以5个学科的SCI期刊和论文为研究对象,取不同底数的对数对每一学科论文被引频次进行转换,计算各期刊对数矫正影响因子(IFlog),以各期刊IFlog除以所在学科所有期刊IFlog平均值,进行学科标准化处理,创建学科标准化影响因子(cnIFlog),探讨cnIFlog在学术期刊跨学科评价中的优越性。研究结果显示,5个学科期刊的IFlog均呈正态分布,且无论同一学科还是不同学科期刊的IFlog1.5、IFln、IFlog5、IFlog10之间均呈100%正相关(r=1.000,P=0.000)。与影响因子(IF2018)、平均影响因子百分位(average impact factor percentile,aJIFP)、期刊PR8指数(journal index of eight percentile rank classes,JIPR8)、IFlog和相对影响因子(relative IF2018,rIF2018)等指标相比,cnIFlog1.5(category normalization for IFlog1.5)在5个学科期刊中变异程度最小、与aJIFP和JIPR8的相关度最高,...     

Some comments on Egghe's derivation of the impact factor distribution

In a recent paper, Egghe [Egghe, L. (in press). Mathematical derivation of the impact factor distribution. Journal of Informetrics] presents a mathematical analysis of the rank-order distribution of journal impact factors. The analysis is based on the central limit theorem. We criticize the empirical relevance of Egghe's analysis. More specifically, we argue that Egghe's analysis relies on an unrealistic assumption and we show that the analysis is not in agreement with empirical data.     

Journal weighted impact factor: A proposal

The impact factor of a journal reflects the frequency with which the journal's articles are cited. It is the best available measure of journal quality. For calculation of impact factor, we just count the number of citations, no matter how prestigious the citing journal is. We think that impact factor as a measure of journal quality, may be improved if in its calculation, we not only take into account the number of citations, but also incorporate a factor reflecting the prestige of the citing journals relative to the cited journal. In calculation of this proposed “weighted impact factor,” each citation has a coefficient (weight) the value of which is 1 if the citing journal is as prestigious as the cited journal; is >1 if the citing journal is more prestigious than the cited journal; and is <1 if the citing journal has a lower standing than the cited journal. In this way, journals receiving many citations from prestigious journals are considered prestigious themselves and those cited by low-status journals seek little credit. By considering both the number of citations and the prestige of the citing journals, we expect the weighted impact factor be a better scientometrics measure of journal quality.     

图书情报领域文献的Altmetrics指标分析

[目的/意义]通过分析某个学科领域中Altmetrics指标的特征,为该领域文献影响力评价提供更加科学合理的指标体系。[方法/过程]定位于图书情报领域,选取Scopus、Altmetric.com进行文献被引频次及Altmetrics指标值的采集,对数据进行统计分析、聚类分析和内容分析。[结果/结论]在众多Altmetrics指标中,Mendeley和Twitter更适合于对图书情报领域文献的影响力做出评价;Mendeley和Twitter中文献的使用群体、文献主题、内容和期刊分布都存在明显的差异性;Twitter适合对文献的社会影响力做出判断,Mendeley更适用于文献的学术影响力评价;不同工具的流行程度存在地域差异,利用Altmetrics指标时应考虑该指标对文献影响力的评价是否存在地域缺失。     

Coverage and citation impact of oncological journals in the Web of Science and Scopus

This paper reviews a number of studies comparing Thomson Scientific’s Web of Science (WoS) and Elsevier’s Scopus. It collates their journal coverage in an important medical subfield: oncology. It is found that all WoS-covered oncological journals (n = 126) are indexed in Scopus, but that Scopus covers many more journals (an additional n = 106). However, the latter group tends to have much lower impact factors than WoS covered journals. Among the top 25% of sources with the highest impact factors in Scopus, 94% is indexed in the WoS, and for the bottom 25% only 6%. In short, in oncology the WoS is a genuine subset of Scopus, and tends to cover the best journals from it in terms of citation impact per paper. Although Scopus covers 90% more oncological journals compared to WoS, the average Scopus-based impact factor for journals indexed by both databases is only 2.6% higher than that based on WoS data. Results reflect fundamental differences in coverage policies: the WoS based on Eugene Garfield’s concepts of covering a selective set of most frequently used (cited) journals; Scopus with broad coverage, more similar to large disciplinary literature databases. The paper also found that ‘classical’, WoS-based impact factors strongly correlate with a new, Scopus-based metric, SCImago Journal Rank (SJR), one of a series of new indicators founded on earlier work by Pinski and Narin [Pinski, G., & Narin F. (1976). Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing and Management, 12, 297–312] that weight citations according to the prestige of the citing journal (Spearman’s rho = 0.93). Four lines of future research are proposed.     

Citing-side normalization of journal impact: A robust variant of the Audience Factor

The principle of a new type of impact measure was introduced recently, called the “Audience Factor” (AF). It is a variant of the journal impact factor where emitted citations are weighted inversely to the propensity to cite of the source. In the initial design, propensity was calculated using the average length of bibliography at the source level with two options: a journal-level average or a field-level average. This citing-side normalization controls for propensity to cite, the main determinant of impact factor variability across fields. The AF maintains the variability due to exports–imports of citations across field and to growth differences. It does not account for influence chains, powerful approaches taken in the wake of Pinski–Narin's influence weights. Here we introduce a robust variant of the audience factor, trying to combine the respective advantages of the two options for calculating bibliography lengths: the classification-free scheme when the bibliography length is calculated at the individual journal level, and the robustness and avoidance of ad hoc settings when the bibliography length is averaged at the field level. The variant proposed relies on the relative neighborhood of a citing journal, regarded as its micro-field and assumed to reflect the citation behavior in this area of science. The methodology adopted allows a large range of variation of the neighborhood, reflecting the local citation network, and partly alleviates the “cross-scale” normalization issue. Citing-side normalization is a general principle which may be extended to other citation counts.     

EBSCO's Communication & Mass Media Complete: An Appreciable Improvement Over Previous Communication Studies Indexing?

ABSTRACT

In a prior edition of this study, we examined whether the established online communication studies indexes—Communication Abstracts, ComIndex, and ComAbstracts—provided a good avenue of access to the journal literature that researchers in the field cite and whether, where the current journal literature was concerned, that avenue of access might be equal or superior to that provided by large, multisubject online indexes. In this iteration of the study, we similarly address EBSCO's new product for communication studies, Communication & Mass Media Complete.     

An evaluation of information behaviour studies through the Scholarly Capital Model

Influence and capital are two concepts used to evaluate scholarly outputs, and these can be measured using the Scholarly Capital Model as a modelling tool. The tool looks at the concepts of connectedness, venue representation, and ideational influence using centrality measures within a social network. This research used co‐authorships and h‐indices to investigate authors who have published papers in the field of information behaviour between 1980 and 2015 as extracted from Web of Science. The findings show a relationship between the authors’ connectedness and the venue (journal) representation. It could be seen that the venue (journal) influences the chance of citation, and equally, the prestige (centrality) of authors probably raises the citations of the journals. The research also shows a significant positive relationship between the venue representation and ideational influence. This means that a research work that is published in a highly cited journal will find more visibility and will receive more citations.