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1.
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   

2.
《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   

3.
In the present work we introduce a modification of the h-index for multi-authored papers with contribution based author name ranking. The modified h-index is denoted by hmc-index. It employs the framework of the hm-index, which in turn is a straightforward modification of the Hirsch index, proposed by Schreiber. To retain the merit of requiring no additional rearrangement of papers in the hm-index and in order to overcome its shortage of benefiting secondary authors at the expense of primary authors, hmc-index uses combined credit allocation (CCA) to replace fractionalized counting in the hm-index. The hm-index is a special form of hmc-index and fits for papers with equally important authors or alphabetically ordered authorship. There is a possibility of an author of lower contribution to the whole scientific community obtaining a higher hmc-index. Rational hmc-index, denoted by hmcr-index, can avoid it. A fictitious example as a model case and two empirical cases are analyzed. The correlations of the hmcr-index with the h-index and its several variants considering multiple co-authorship are inspected with 30 researchers’ citation data. The results show that the hmcr-index is more reasonable for authors with different contributions. A researcher playing more important roles in significant work will obtain higher hmcr-index.  相似文献   

4.
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   

5.
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   

6.
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   

7.
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   

8.
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   

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 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   

11.
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   

12.
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   

13.
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   

14.
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   

15.
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   

16.
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   

17.
Based on an idea by Kosmulski, Franceschini et al. (2012, Scientometrics 92(3), 621–641) propose to classify a publication as “successful” when it receives more citations than a specific comparison term (CT). In the intention of the authors CT should be a suitable estimate of the number of citations that a publication – in a certain scientific context and period of time – should potentially achieve. According to this definition, the success-index is defined as the number of successful papers, among a group of publications examined, such as those associated to a scientist or a journal. In the first part of the paper, the success-index is recalled, discussing its properties and limitations. Next, relying on the theory of Information Production Processes (IPPs), an informetric model of the index is formulated, for a better comprehension of the index and its properties. Particular emphasis is given to a theoretical sensitivity analysis of the index.  相似文献   

18.
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19.
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   

20.
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   

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