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 265 毫秒
1.
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   

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.
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 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.
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   

6.
Research was undertaken that examined what, if any, correlation there was between the h-index and rankings by peer assessment, and what correlation there was between the 2008 UK RAE rankings and the collective h-index of submitting departments. About 100 international scholars in Library and Information Science were ranked by their peers on the quality of their work. These rankings were correlated with the h and g scores the scholars had achieved. The results showed that there was a correlation between their median rankings and the indexes. The 2008 RAE grade point averages (GPA) achieved by departments from three UoAs – Anthropology, Library and Information Management and Pharmacy were compared with each of their collective h and g index scores. Results were mixed, with a strong correlation between pharmacy departments and index scores, followed by library and information management to anthropology where negative and non-significant results were found. Taken together, the findings from the research indicate that individual ranking by peer assessment and their h-index or variants was generally good. Results for the RAE 2008 gave correlations between GPA and successive versions of the h-index which varied in strength, except for anthropology where, it is suggested detailed cited reference searches must be undertaken to maximise citation counts.  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.
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   

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 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   

11.
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   

12.
In this paper a generalisation of the h-index and g-index is given on the basis of non-negative real-valued functionals defined on subspaces of the vector space generated by the ordered samples. Several Hirsch-type measures are defined and their basic properties are analysed. Empirical properties are illustrated using examples from the micro- and meso-level. Among these measures, the h-index proved the most, the arithmetic and geometric g-indices, the least robust measures. The μ-index and the harmonic g-index provide more balanced results and are still robust enough.  相似文献   

13.
This article reviews the debate within bibliometrics regarding the h-index. Despite its popularity as a decision-making tool within higher education, the h-index has become increasingly controversial among specialists. Fundamental questions remain regarding the extent to which the h-index actually measures what it sets out to measure. Unfortunately, many aspects of this debate are confined to highly technical discussions in specialised journals. This article explains in simple terms exactly why a growing number of bibliometricians are sceptical that the h-index is a useful tool for evaluating researchers. It concludes that librarians should be cautious in their recommendations regarding this metric, at least until better evidence becomes available.  相似文献   

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.
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.
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.
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   

18.
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   

19.
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   

20.
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   

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