首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 409 毫秒
1.
The Hirsch index is a number that synthesizes a researcher's output. It is the maximum number h such that the researcher has h papers with at least h citations each. Woeginger [Woeginger, G. J. (2008a). An axiomatic characterization of the Hirsch-index. Mathematical Social Sciences, 56(2), 224–232; Woeginger, G. J. (2008b). A symmetry axiom for scientific impact indices. Journal of Informetrics, 2(3), 298–303] characterizes the Hirsch index when indices are assumed to be integer-valued. In this note, the Hirsch index is characterized, when indices are allowed to be real-valued, by adding to Woeginger's monotonicity two axioms in a way related to the concept of monotonicity.  相似文献   

2.
In order to take multiple co-authorship appropriately into account, a straightforward modification of the Hirsch index was recently proposed. Fractionalised counting of the papers yields an appropriate measure which is called the hm-index. The effect of this procedure is compared in the present work with other variants of the h-index and found to be superior to the fractionalised counting of citations and to the normalization of the h-index with the average number of authors in the h-core. Three fictitious examples for model cases and one empirical case are analysed.  相似文献   

3.
The following seniority-independent Hirsch-type index has been defined. A scientist has index hpd if hpd of his/her papers have at least hpd citations per decade each, and his/her other papers have less than hpd + 1 citations per decade each. In contrast with the original h-index, which steadily increases in time, hpd of a mature scientist is nearly constant over many years, and hpd of an inactive scientist slowly declines. Therefore hpd is suitable to compare the scientific output of scientists in different ages.  相似文献   

4.
The definition of the g-index is as arbitrary as that of the h-index, because the threshold number g2 of citations to the g most cited papers can be modified by a prefactor at one's discretion, thus taking into account more or less of the highly cited publications within a dataset. In a case study I investigate the citation records of 26 physicists and show that the prefactor influences the ranking in terms of the generalized g-index less than for the generalized h-index. I propose specifically a prefactor of 2 for the g-index, because then the resulting values are of the same order of magnitude as for the common h-index. In this way one can avoid the disadvantage of the original g-index, namely that the values are usually substantially larger than for the h-index and thus the precision problem is substantially larger; while the advantages of the g-index over the h-index are kept. Like for the generalized h-index, also for the generalized g-index different prefactors might be more useful for investigations which concentrate only on top scientists with high citation frequencies or on junior researchers with small numbers of citations.  相似文献   

5.
We axiomatize the well-known Hirsch index (h-index), which evaluates researcher productivity and impact on a field, and formalize a new axiom called head-independence. Under head-independence, a decrease, to some extent, in the number of citations of “frequently cited papers” has no effect on the index. Together with symmetry and axiom D, head-independence uniquely characterizes the h-index on a certain domain of indices. Some relationships between our axiomatization and those in the literature are also investigated.  相似文献   

6.
We show that the h-index, g-index, ψ-index, and p-index, are related through the inequalities: h ≤ p ≤ g ≤ ψ. Moreover, this relation is proved theoretically in the mathematical framework of Lotkaian informetrics and is verified empirically by using two datasets from the Web of Science in the fields of electrochemistry and gerontology. For quantifying their relations, we estimate the g-index, ψ-index, and their cores and ratios of cores via a second-order Taylor series when the e-index, h-index, and C1 (the maximum number of citations received by a paper) are known. Then we find for the two empirical cases, that ratios of cores and average citations are approximately stable. Compared with the g-index, the offset-ability of the h-index decreases by 20% but the average citations increase by 20%. A similar observation holds for the comparison of the g-index and ψ-index. To explore the possible applications of cores of different indices, we apply them to extract the core structure of a network. The h-core is the most efficient, while the ψ-core includes more nodes with high betweenness.  相似文献   

7.
The definitions of the rational and real-valued variants of the h-index and g-index are reviewed. It is shown how they can be obtained both graphically and by calculation. Formulae are derived expressing the exact relations between the h-variants and between the g-variants. Subsequently these relations are examined. In a citation context the real h-index is often, but not always, smaller than the rational h-index. It is also shown that the relation between the real and the rational g-index depends on the number of citations of the article ranked g + 1. Maximum differences between h, hr and hrat on the one hand and between g, gr and grat on the other are determined.  相似文献   

8.
Scientific impact indexes like h are responsive to two parameters: the researcher's productivity given by the number of her published papers (an aspect of quantity) and citations (an aspect of quality). In this paper I prove that the two parameters can be treated separately: the index h can be axiomatized by appealing (1) only to axioms that allow for productivity changes, but do not require taking into account distinct situations in which a researcher's papers received different numbers of citations or (2) only to axioms that allow for changes in the number of citations received by the researcher's papers, but do not require changes in scientific productivity. The axioms used are weak. Specifically, monotonicity is avoided.  相似文献   

9.
This study describes the meaning of and the formula for S-index, which is a novel evaluation index based on the number of citations of each article in a particular journal and the rank of the article according to the number of citations. This study compares S-index with Impact Factor (IF), which is the most well-known evaluation index, using the Korea Citation Index data. It is shown that S-index is positively correlated with the number of articles published in a journal. Tapered h-index (hT-index), which is based on all articles of a journal like S-index, is compared with S-index. It is shown that there is a very strong positive correlation between S-index and hT-index. Although S-index is similar to hT-index, S-index has a slightly better differentiating power and ranks the journal with evenly cited articles higher.  相似文献   

10.
The arbitrariness of the h-index becomes evident, when one requires q × h instead of h citations as the threshold for the definition of the index, thus changing the size of the core of the most influential publications of a dataset. I analyze the citation records of 26 physicists in order to determine how much the prefactor q influences the ranking. Likewise, the arbitrariness of the highly-cited-publications indicator is due to the threshold value, given either as an absolute number of citations or as a percentage of highly cited papers. The analysis of the 26 citation records shows that the changes in the rankings in dependence on these thresholds are rather large and comparable with the respective changes for the h-index.  相似文献   

11.
We show that usually the influence on the Hirsch index of missing highly cited articles is much smaller than the number of missing articles. This statement is shown by a combinatorial argument. We further show, by using a continuous power law model, that the influence of missing articles is largest when the total number of publications is small, and non-existing when the number of publications is very large. The same conclusion can be drawn for missing citations. Hence, the h-index is resilient to missing articles and to missing citations.  相似文献   

12.
This paper analyzes several well-known bibliometric indices using an axiomatic approach. We concentrate on indices aiming at capturing the global impact of a scientific output and do not investigate indices aiming at capturing an average impact. Hence, the indices that we study are designed to evaluate authors or groups of authors but not journals. The bibliometric indices that are studied include classic ones such as the number of highly cited papers as well as more recent ones such as the h-index and the g-index. We give conditions that characterize these indices, up to the multiplication by a positive constant. We also study the bibliometric rankings that are induced by these indices. Hence, we provide a general framework for the comparison of bibliometric rankings and indices.  相似文献   

13.
The process of assessing individual authors should rely upon a proper aggregation of reliable and valid papers’ quality metrics. Citations are merely one possible way to measure appreciation of publications. In this study we propose some new, SJR- and SNIP-based indicators, which not only take into account the broadly conceived popularity of a paper (manifested by the number of citations), but also other factors like its potential, or the quality of papers that cite a given publication. We explore the relation and correlation between different metrics and study how they affect the values of a real-valued generalized h-index calculated for 11 prominent scientometricians. We note that the h-index is a very unstable impact function, highly sensitive for applying input elements’ scaling. Our analysis is not only of theoretical significance: data scaling is often performed to normalize citations across disciplines. Uncontrolled application of this operation may lead to unfair and biased (toward some groups) decisions. This puts the validity of authors assessment and ranking using the h-index into question. Obviously, a good impact function to be used in practice should not be as much sensitive to changing input data as the analyzed one.  相似文献   

14.
The scientific impact of a publication can be determined not only based on the number of times it is cited but also based on the citation speed with which its content is noted by the scientific community. Here we present the citation speed index as a meaningful complement to the h index: whereas for the calculation of the h index the impact of publications is based on number of citations, for the calculation of the speed index it is the number of months that have elapsed since the first citation, the citation speed with which the results of publications find reception in the scientific community. The speed index is defined as follows: a group of papers has the index s if for s of its Np papers the first citation was at least s months ago, and for the other (Np ? s) papers the first citation was ≤s months ago.  相似文献   

15.
A variety of bibliometric measures have been proposed to quantify the impact of researchers and their work. The h-index is a notable and widely used example which aims to improve over simple metrics such as raw counts of papers or citations. However, a limitation of this measure is that it considers authors in isolation and does not account for contributions through a collaborative team. To address this, we propose a natural variant that we dub the Social h-index. The idea is to redistribute the h-index score to reflect an individual's impact on the research community. In addition to describing this new measure, we provide examples, discuss its properties, and contrast with other measures.  相似文献   

16.
  相似文献   

17.
Hirsch's h-index seeks to give a single number that in some sense summarizes an author's research output and its impact. Essentially, the h-index seeks to identify the most productive core of an author's output in terms of most received citations. This most productive set we refer to as the Hirsch core, or h-core. Jin's A-index relates to the average impact, as measured by the average number of citations, of this “most productive” core. In this paper, we investigate both the total productivity of the Hirsch core – what we term the size of the h-core – and the A-index using a previously proposed stochastic model for the publication/citation process, emphasising the importance of the dynamic, or time-dependent, nature of these measures. We also look at the inter-relationships between these measures. Numerical investigations suggest that the A-index is a linear function of time and of the h-index, while the size of the Hirsch core has an approximate square-law relationship with time, and hence also with the A-index and the h-index.  相似文献   

18.
A recently suggested modification of the g-index is analysed in order to take multiple coauthorship appropriately into account. By fractionalised counting of the papers one can obtain an appropriate measure which I call gm-index. Two fictitious examples for model cases and two empirical cases are analysed. The results are compared with two other variants of the g-index which have also recently been proposed. Only the gm-index shows the correct behaviour when datasets are aggregated. The interpolated and continuous versions of the g-index and its variants are also discussed. For an intuitive comparison of the determination of the investigated variants of the h-index and the g-index, a visualization of the citation records is utilized.  相似文献   

19.
  相似文献   

20.
This paper presents the first meta-analysis of studies that computed correlations between the h index and variants of the h index (such as the g index; in total 37 different variants) that have been proposed and discussed in the literature. A high correlation between the h index and its variants would indicate that the h index variants hardly provide added information to the h index. This meta-analysis included 135 correlation coefficients from 32 studies. The studies were based on a total sample size of N = 9005; on average, each study had a sample size of n = 257. The results of a three-level cross-classified mixed-effects meta-analysis show a high correlation between the h index and its variants: Depending on the model, the mean correlation coefficient varies between .8 and .9. This means that there is redundancy between most of the h index variants and the h index. There is a statistically significant study-to-study variation of the correlation coefficients in the information they yield. The lowest correlation coefficients with the h index are found for the h index variants MII and m index. Hence, these h index variants make a non-redundant contribution to the h index.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号