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1.
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   

2.
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   

3.
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   

4.
The minimum configuration to have a h-index equal to h is h papers each having h citations, hence h2 citations in total. To increase the h-index to h + 1 we minimally need (h + 1)2 citations, an increment of I1(h) = 2h + 1. The latter number increases with 2 per unit increase of h. This increment of the second order is denoted I2(h) = 2.If we define I1 and I2 for a general Hirsch configuration (say n papers each having f(n) citations) we calculate I1(f) and I2(f) similarly as for the h-index. We characterize all functions f for which I2(f) = 2 and show that this can be obtained for functions f(n) different from the h-index. We show that f(n) = n (i.e. the h-index) if and only if I2(f) = 2, f(1) = 1 and f(2) = 2.We give a similar characterization for the threshold index (where n papers have a constant number C of citations). Here we deal with second order increments I2(f) = 0.  相似文献   

5.
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   

6.
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   

7.
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   

8.
《Journal of Informetrics》2019,13(2):515-539
Counting of number of papers, of citations and the h-index are the simplest bibliometric indices of the impact of research. We discuss some improvements. First, we replace citations with individual citations, fractionally shared among co-authors, to take into account that different papers and different fields have largely different average number of co-authors and of references. Next, we improve on citation counting applying the PageRank algorithm to citations among papers. Being time-ordered, this reduces to a weighted counting of citation descendants that we call PaperRank. We compute a related AuthorRank applying the PageRank algorithm to citations among authors. These metrics quantify the impact of an author or paper taking into account the impact of those authors that cite it. Finally, we show how self- and circular-citations can be eliminated by defining a closed market of Citation-coins. We apply these metrics to the InSpire database that covers fundamental physics, presenting results for papers, authors, journals, institutes, towns, countries for all-time and in recent time periods.  相似文献   

9.
Despite the huge amount of literature concerning the h-index, few papers have been devoted to its statistical analysis when a probabilistic distribution is assumed for citation counts. The present contribution mainly aims to divulge the inferential techniques recently introduced by Pratelli et al. (2012), by explaining the details for proper point and set estimation of the theoretical h-index. Moreover, some new achievements on simultaneous inference – addressed to produce suitable scholar comparisons – are carried out. Finally, the analysis of the citation dataset for the Nobel Laureates (in the last five years) and for the Fields medallists (from 2002 onward) is considered in order to exemplify the theoretical issues.  相似文献   

10.
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   

11.
A variant of the h-index, named the stochastic h-index, is proposed. This new index is obtained by adding to the h-index the probability, under a specific stochastic model, that the h-index will increase by one or more within a given time interval. The stochastic h-index thus extends the h-index to the real line and has a direct interpretation as the distance to the next higher index value. We show how the stochastic h-index can be evaluated and compare it with other variants of the h-index which purportedly indicate the distance to a higher h-index.  相似文献   

12.
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   

13.
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14.
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   

15.
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   

16.
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   

17.
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   

18.
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   

19.
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   

20.
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   

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