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1.
Journal weighted impact factor: A proposal 总被引：3，自引：0，他引：3
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. 相似文献
2.
《Journal of Informetrics》2014,8(2):421-430
Unlike Impact Factors (IF), Article Influence (AI) scores assign greater weight to citations that appear in highly cited journals. The natural sciences tend to have higher citation rates than the social sciences. We might therefore expect that relative to IF, AI overestimates the citation impact of social science journals in subfields that are related to (and presumably cited in) higher-impact natural science disciplines. This study evaluates that assertion through a set of simple and multiple regressions covering seven social science disciplines: anthropology, communication, economics, education, library and information science, psychology, and sociology. Contrary to expectations, AI underestimates 5IF (five-year Impact Factor) for journals in science-related subfields such as scientific communication, science education, scientometrics, biopsychology, and medical sociology. Journals in these subfields have low AI scores relative to their 5IF values. Moreover, the effect of science-related status is considerable—typically 0.60 5IF units or 0.50 SD. This effect is independent of the more general finding that AI scores underestimate 5IF for higher-impact journals. It is also independent of the very modest curvilinearity in the relationship between AI and 5IF. 相似文献
3.
《Journal of Informetrics》2014,8(2):406-418
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
4.
为评价H指数与影响因子、总被引频次的关系,以2009年《中国期刊引证报告》（扩刊版）中166种医学期刊的H指数、影响因子、总被引频次、引用刊数和来源文献量为源数据,采用SPSSl6．0软件作线性、对数、二次多项式、三次多项式回归拟合和Logistic回归。二维散点图和曲线回归拟合分析均发现,H指数与影响因子、总被引频次、引用刊数呈密切相关,但与来源文献量的相关性不强。因此,H指数、影响因子、总被引频次应相互补充,共同用于医学类期刊学术影响力的评价。 相似文献
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Manolis Antonoyiannakis 《Journal of Informetrics》2018,12(4):1072-1088
Citation averages, and Impact Factors (IFs) in particular, are sensitive to sample size. Here, we apply the Central Limit Theorem to IFs to understand their scale-dependent behavior. For a journal of n randomly selected papers from a population of all papers, we expect from the Theorem that its IF fluctuates around the population average μ, and spans a range of values proportional to , where σ2 is the variance of the population's citation distribution. The dependence has profound implications for IF rankings: The larger a journal, the narrower the range around μ where its IF lies. IF rankings therefore allocate an unfair advantage to smaller journals in the high IF ranks, and to larger journals in the low IF ranks. As a result, we expect a scale-dependent stratification of journals in IF rankings, whereby small journals occupy the top, middle, and bottom ranks; mid-sized journals occupy the middle ranks; and very large journals have IFs that asymptotically approach μ. We obtain qualitative and quantitative confirmation of these predictions by analyzing (i) the complete set of 166,498 IF & journal-size data pairs in the 1997–2016 Journal Citation Reports of Clarivate Analytics, (ii) the top-cited portion of 276,000 physics papers published in 2014–2015, and (iii) the citation distributions of an arbitrarily sampled list of physics journals. We conclude that the Central Limit Theorem is a good predictor of the IF range of actual journals, while sustained deviations from its predictions are a mark of true, non-random, citation impact. IF rankings are thus misleading unless one compares like-sized journals or adjusts for these effects. We propose the Φ index, a rescaled IF that accounts for size effects, and which can be readily generalized to account also for different citation practices across research fields. Our methodology applies to other citation averages that are used to compare research fields, university departments or countries in various types of rankings. 相似文献
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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
8.
JCR 5年期影响因子实证分析 总被引：1，自引：0，他引：1
9.
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,具有理想的区分度和稳定性。无论同一学科还是跨学科期刊评价,cnIFlog1.5均是理想的评价指标。 相似文献
10.
社会科学引文的离散性研究——基于JCR社科版指标分析 总被引：1，自引：0，他引：1
《期刊引证报告》(JCR)是美国科技信息研究所于1975年出版的一种独特的多学科期刊分析评价工具。通过对2005年的JCR社会科学版数据的统计分析可知,社会科学引文在基本符合布拉德福定律的情况下离散程度有所缩小,在社会科学领域较多的期刊承担着学术交流任务,因此不能笼统地说社会科学引文在期刊中的分布符合布拉德福定律,而应该注意到它的集中分散有一定的特殊性。 相似文献
11.
Do academic journals favor authors who share their institutional affiliation? To answer this question we examine citation counts, as a proxy for paper quality, for articles published in four leading international relations journals during the years 2000–2015. We compare citation counts for articles written by “in-group members” (authors affiliated with the journal’s publishing institution) versus “out-group members” (authors not affiliated with that institution). Articles written by in-group authors received 18% to 49% fewer Web of Science citations when published in their home journal (International Security or World Politics) vs. an unaffiliated journal, compared to out-group authors. These results are mainly driven by authors who received their PhDs from Harvard or MIT. The findings show evidence of a bias within some journals towards publishing papers by faculty from their home institution, at the expense of paper quality. 相似文献
12.
JCR五年期影响因子探析 总被引：6，自引：0，他引：6
使用期刊引证报告(JCR)6015种期刊数据,以统计学方法探索性地分析5年期影响因子IF5的特点.结果显示,IF5作为具有代表性的平均性期刊评价指标,能更好地反映多数期刊被引高峰,总体符合布拉德福分布.IF5与2年期影响因子IF存在排序相关,也有显著统计学差异,两者测评结果在较好和较差期刊上相对一致,但在多数水平居中的期刊上存在区别.最后,给出Ifa指数测度两种影响因子的差别和Ifb指数综合两种影响因子的评价信息. 相似文献
13.
The paper introduces a new journal impact measure called The Reference Return Ratio (3R). Unlike the traditional Journal Impact Factor (JIF), which is based on calculations of publications and citations, the new measure is based on calculations of bibliographic investments (references) and returns (citations). A comparative study of the two measures shows a strong relationship between the 3R and the JIF. Yet, the 3R appears to correct for citation habits, citation dynamics, and composition of document types – problems that typically are raised against the JIF. In addition, contrary to traditional impact measures, the 3R cannot be manipulated ad infinitum through journal self-citations. 相似文献
14.
Konstantinos Petridis Chrisovalantis Malesios Garyfallos Arabatzis Emmanuel Thanassoulis 《Journal of Informetrics》2013,7(2):505-521
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. 相似文献
15.
P指数用于中文社会科学学术期刊评价的适用性分析 总被引：1，自引：0，他引：1
认为P指数在期刊绩效评价中体现了数量(被引次数C)与质量(平均被引率C/N)的平衡,应用P指数进行学术期刊评价是一种有益的探索。以法学期刊和教育学期刊为研究对象,对比分析P指数在不同学科期刊中与期刊载文量(N),被引次数(C),自被引率(SCR),5年影响因子(IF5)、期刊h指数、特征因子组合(EFS,AIS)等指标的差异,进行相关性分析,并得出以下结论:P指数简洁易计算,区分度好、支持动态变化排名、与多个关键评价指标相关性好,且在优秀学术期刊识别方面具有较好的可靠性,具有一定的现实应用前景。 相似文献
16.
针对目前各图书馆的核心期刊评价不能准确反映读者对期刊的实际需求与馆藏期刊实际利用情况的问题,及不同署名位次的作者对文后参考文献的利用程度不同,提出了基于期刊加权被引次数的馆藏期刊评价方法,并以第二军医大学作者引用较多的风湿病学西文期刊为例进行期刊评价,结果证明利用该方法进行期刊评价要优于基于引文分析的传统期刊评价方法。 相似文献
17.
收集 Web of Science（WoS）数据库的高被引撤销论文数据,分析其分布规律和引证特征。结果发现,TOP20%高被引撤销论文430篇,分布于31个国家,多学科领域最多,35种期刊>3篇。高被引撤销论文撤销时滞和撤销论文总被引频次相关性较弱（P=0.014）,和撤销前被引频次相关性较强（P=0.000）。期刊 IF和撤销论文数量、撤销论文总被引频次、撤销论文篇均被引频次正相关（P=0.017、P=0.000、P=0.005）。撤销后年均被引频次低于撤销前（P=0.000）。本研究说明 IF 高的期刊发表的撤销论文对学术界带来的负面影响较大,撤销时滞延长增加了撤销前引用,撤销起到了一定的净化效果,但是净化效果还不理想,建议国内外学者加强对撤销论文及其不良影响的关注。 相似文献
18.
《Journal of Informetrics》2014,8(2):318-328
Citation based approaches, such as the impact factor and h-index, have been used to measure the influence or impact of journals for journal rankings. A survey of the related literature for different disciplines shows that the level of correlation between these citation based approaches is domain dependent. We analyze the correlation between the impact factors and h-indices of the top ranked computer science journals for five different subjects. Our results show that the correlation between these citation based approaches is very low. Since using a different approach can result in different journal rankings, we further combine the different results and then re-rank the journals using a combination method. These new ranking results can be used as a reference for researchers to choose their publication outlets. 相似文献
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《Journal of Informetrics》2020,14(1):101007
This study compares the two-year impact factor (JIF2), JIF2 without journal self-citation (JIF2_noJSC), five-year impact factor (JIF5), eigenfactor score and article influence score (AIS) and investigates their relative changes with time. JIF2 increased faster than JIF5 overall. The relative change between JIF2 and JIF_noJSC shows that the control of JCR over journal self-citation is effective to some extent. JIF5 is more discriminative than JIF2. The correlation between JIF5 and AIS is stronger than that between JIF5 and the eigenfactor score. The relative change in journal rank according to different indicators varies with the ratio of the indicators and can be up to 60 % of the number of journals in a subject category. There is subject category discrepancy in the average AIS and its change over time. Through the screening of journals according to variations in the ratio of JIF2 to JIF5 for journals in individual subject categories, we found that journals in the same subject categories can have considerably different citation patterns. To provide a fair comparison of journals in individual subject categories, we argue that it is better to replace JIF2 with the ready-made JIF5 when ranking journals. 相似文献