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1.
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   

2.
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   

3.
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   

4.
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   

5.
From the way that it was initially defined (Hirsch, 2005), the h-index naturally encourages focus on the most highly cited publications of an author and this in turn has led to (predominantly) a rank-based approach to its investigation. However, Hirsch (2005) and Burrell (2007a) both adopted a frequency-based approach leading to general conjectures regarding the relationship between the h-index and the author's publication and citation rates as well as his/her career length. Here we apply the distributional results of Burrell, 2007a, Burrell, 2013b to three published data sets to show that a good estimate of the h-index can often be obtained knowing only the number of publications and the number of citations. (Exceptions can occur when an author has one or more “outliers” in the upper tail of the citation distribution.) In other words, maybe the main body of the distribution determines the h-index, not the wild wagging of the tail. Furthermore, the simple geometric distribution turns out to be the key.  相似文献   

6.
The aim of the study is to explore the effects of the increase in the number of publications or citations on several impact indicators by a single journal paper or citation. The possible change of the h-index, A-index, R-index, π-index, π-rate, Journal Paper Citedness (JPC), and Citation Distribution Score (CDS) is followed by models. Particular attention is given to the increase of the indices by a single plus citation. The results obtained by the “successively built-up indicator” model show that with increasing number of citations or self-citations the indices may increase substantially.  相似文献   

7.
The aim of this brief communication is to reply to a letter by Kosmulski (Journal of Informetrics 6(3):368–369, 2012), which criticizes a recent indicator called “success-index”. The most interesting features of this indicator, presented in Franceschini et al. (Scientometrics, in press), are: (i) allowing the selection of an “elite” subset from a set of publications and (ii) implementing the field-normalization at the level of an individual publication. We show that the Kosmulski's criticism is unfair and inappropriate, as it is the result of a misinterpretation of the indicator.  相似文献   

8.
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   

9.
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   

10.
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   

11.
The Hirsch index and the Egghe index are both numbers that synthesize a researcher's output. The h-index associated with researcher r is the maximum number h such that r has h papers with at least h citations each. The g-index is the maximum number g of papers by r such that the average number of citations of the g papers is at least g. Both indices are characterized in terms of four axioms. One identifies outputs deserving index at most one. A second one establishes a strong monotonicity condition. A third one requires the index to satisfy a property of subadditivity. The last one consists of a monotonicity condition, for the h-index, and an aggregate monotonicity condition, for the g-index.  相似文献   

12.
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   

13.
Based on the rank-order citation distribution of e.g. a researcher, one can define certain points on this distribution, hereby summarizing the citation performance of this researcher. Previous work of Glänzel and Schubert defined these so-called “characteristic scores and scales” (CSS), based on average citation data of samples of this ranked publication–citation list.In this paper we will define another version of CSS, based on diverse h-type indices such as the h-index, the g-index, the Kosmulski's h(2)-index and the g-variant of it, the g(2)-index.Mathematical properties of these new CSS are proved in a Lotkaian framework. These CSS also provide an improvement of the single h-type indices in the sense that they give h-type index values for different parts of the ranked publication–citation list.  相似文献   

14.
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   

15.
In a recent work by Anderson, Hankin, and Killworth (2008), Ferrers diagrams and Durfee squares are used to represent the scientific output of a scientist and construct a new h-based bibliometric indicator, the tapered h-index (hT). In the first part of this paper we examine hT, identifying its main drawbacks and weaknesses: an arbitrary scoring system and an illusory increase in discrimination power compared to h. Subsequently, we propose a new bibliometric tool, the citation triad (CT), that better exploits the information contained in a Ferrers diagram, giving a synthetic overview of a scientist's publication output. The advantages of this new approach are discussed in detail. Argument is supported by several examples based on empirical data.  相似文献   

16.
Scholarly citations – widely seen as tangible measures of the impact and significance of academic papers – guide critical decisions by research administrators and policy makers. The citation distributions form characteristic patterns that can be revealed by big-data analysis. However, the citation dynamics varies significantly among subject areas, countries etc. The problem is how to quantify those differences, separate global and local citation characteristics. Here, we carry out an extensive analysis of the power-law relationship between the total citation count and the h-index to detect a functional dependence among its parameters for different science domains. The results demonstrate that the statistical structure of the citation indicators admits representation by a global scale and a set of local exponents. The scale parameters are evaluated for different research actors – individual researchers and entire countries – employing subject- and affiliation-based divisions of science into domains. The results can inform research assessment and classification into subject areas; the proposed divide-and-conquer approach can be applied to hidden scales in other power-law systems.  相似文献   

17.
The h-index has been shown to have predictive power. Here I report results of an empirical study showing that the increase of the h-index with time often depends for a long time on citations to rather old publications. This inert behavior of the h-index means that it is difficult to use it as a measure for predicting future scientific output.  相似文献   

18.
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   

19.
Most current h-type indicators use only a single number to measure a scientist's productivity and impact of his/her published works. Although a single number is simple to calculate, it fails to outline his/her academic performance varying with time. We empirically study the basic h-index sequence for cumulative publications with consideration of the yearly citation performance (for convenience, referred as L-Sequence). L-Sequence consists of a series of L factors. Based on the citations received in the corresponding individual year, every factor along a scientist's career span is calculated by using the h index formula. Thus L-Sequence shows the scientist's dynamic research trajectory and provides insight into his/her scientific performance at different periods. Furthermore, L, summing up all factors of L-Sequence, is for the evaluation of the whole research career as alternative to other h-index variants. Importantly, the partial factors of the L-Sequence can be adapted for different evaluation tasks. Moreover, L-Sequence could be used to highlight outstanding scientists in a specific period whose research interests can be used to study the history and trends of a specific discipline.  相似文献   

20.
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   

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