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1.
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2.
The h index is a widely used indicator to quantify an individual's scientific research output. But it has been criticized for its insufficient accuracy—the ability to discriminate reliably between meaningful amounts of research output. As a single measure it cannot capture the complete information on the citation distribution over a scientist's publication list. An extensive data set with bibliometric data on scientists working in the field of molecular biology is taken as an example to introduce two approaches providing additional information to the h index: (1) h2 lower, h2 center, and h2 upper are proposed, which allow quantification of three areas within a scientist's citation distribution: the low impact area (h2 lower), the area captured by the h index (h2 center), and the area of publications with the highest visibility (h2 upper). (2) Given the existence of different areas in the citation distribution, the segmented regression model (sRM) is proposed as a method to statistically estimate the number of papers in a scientist's publication list with the highest visibility. However, such sRM values should be compared across individuals with great care.  相似文献   

3.
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   

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.
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   

6.
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   

7.
Hirsch [Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569–16572] has proposed the h index as a single-number criterion to evaluate the scientific output of a researcher. We investigated the convergent validity of decisions for awarding long-term fellowships to post-doctoral researchers as practiced by the Boehringer Ingelheim Fonds (B.I.F.) by using the h index. Our study examined 414 B.I.F. applicants (64 approved and 350 rejected) with a total of 1586 papers. The results of our study show that the applicants’ h indices correlate substantially with standard bibliometric indicators. Even though the h indices of approved B.I.F. applicants on average (arithmetic mean and median) are higher than those of rejected applicants (and with this, fundamentally confirm the validity of the funding decisions), the distributions of the h indices show in part overlaps that we categorized as type I error (falsely drawn approval) or type II error (falsely drawn rejection). Approximately, one-third of the decisions to award a fellowship to an applicant show a type I error, and about one-third of the decisions not to award a fellowship to an applicant show a type II error. Our analyses of possible reasons for these errors show that the applicant's field of study but not personal ties between the B.I.F. applicant and the B.I.F. can increase or decrease the risks for type I and type II errors.  相似文献   

8.
Identifying research fronts is an essential aspect of promoting scientific development. Many researchers choose their research directions and topics by analyzing their field's current research fronts. Many previous researchers have used academic papers or patents to identify research fronts; however, this is potentially outdated and reduces the prospective value of the research front detection. Considering this, this work proposes adapted indicators to conduct research front topic detection based on research grant data, which aims to identify research front topics and forecast trends using path analysis. First, research topics were identified using topic modeling, and then the mapping relations from topics to both fund projects and cross-domain categories were built. Then, research front topics were detected by multi-dimensional measurements, and the evolution of research topics was analyzed using topic evolution visualization to predict development trends. Finally, the Brillouin index was used to measure the cross-domain degree. Our method was evaluated using a dataset from the field of health informatics and was shown to be effective in research front identification. We found that the proposed adapted indicators were informative in identifying the evolutional trends in the health informatics field. In addition, research grants with higher cross-domain degrees are more likely to receive a high amount of funding.  相似文献   

9.
We have studied the efficiency of research in the EU by a percentile-based citation approach that analyzes the distribution of country papers among the world papers. Going up in the citation scale, the frequency of papers from efficient countries increases while the frequency from inefficient countries decreases. In the percentile-based approach, this trend, which is uniform at any citation level, is measured by the ep index that equals the Ptop 1%/Ptop 10% ratio. By using the ep index we demonstrate that EU research on fast-evolving technological topics is less efficient than the world average and that the EU is far from being able to compete with the most advanced countries. The ep index also shows that the USA is well ahead of the EU in both fast- and slow-evolving technologies, which suggests that the advantage of the USA over the EU in innovation is due to low research efficiency in the EU. In accord with some previous studies, our results show that the European Commission’s ongoing claims about the excellence of EU research are based on a wrong diagnosis. The EU must focus its research policy on the improvement of its inefficient research. Otherwise, the future of Europeans is at risk.  相似文献   

10.
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   

11.
Across the various scientific domains, significant differences occur with respect to research publishing formats, frequencies and citing practices, the nature and organisation of research and the number and impact of a given domain's academic journals. Consequently, differences occur in the citations and h-indices of the researchers. This paper attempts to identify cross-domain differences using quantitative and qualitative measures. The study focuses on the relationships among citations, most-cited papers and h-indices across domains and for research group sizes. The analysis is based on the research output of approximately 10,000 researchers in Slovenia, of which we focus on 6536 researchers working in 284 research group programmes in 2008–2012.As comparative measures of cross-domain research output, we propose the research impact cube (RIC) representation and the analysis of most-cited papers, highest impact factors and citation distribution graphs (Lorenz curves). The analysis of Lotka's model resulted in the proposal of a binary citation frequencies (BCF) distribution model that describes well publishing frequencies. The results may be used as a model to measure, compare and evaluate fields of science on the global, national and research community level to streamline research policies and evaluate progress over a definite time period.  相似文献   

12.
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   

13.
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14.
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   

15.
本文以Scientometrics 1991—2010年间刊载的2,045篇论文作为数据样本,分两个时间段研究这20年间科学计量学的知识结构与演进状况,并以此来研究作者文献耦合分析法（ABCA）与作者关键词耦合分析法（AKCA）在揭示学科领域知识结构方面的异同。研究发现,2001—2010年间的科学计量学的知识结构要比1991—2000年间的更加清晰明朗,其研究主题之间更为亲密,相互作用力明显要强。作者排名相关分析、研究主题探测、余弦相似度计算、研究主题变迁等均显示,AKCA与ABCA存在高度相关性;通过因子分析的模型拟合、研究主题的探测与变迁分析,又显示二者略有不同,ABCA可以探寻到比AKCA更多的研究主题,AKCA比ABCA能显示更多的信号来反映学科的技术突破以及研究前沿的进展。因此ABCA与AKCA不可互相替代,二者结合起来是探寻学科知识结构及其发展的理想研究方法。图4。表6。参考文献25。  相似文献   

16.
Are you in h?     
A new method of assessment of scientific papers, scientists, and scientific institutions was defined. The significance of a paper was assessed by the definition of the largest (the most prestigious) set, including that paper in its h-core. The sets of papers were defined by affiliation (country, city, university, department) or by subject (branches and sub-branches of science, journal). The inclusion of a paper in the h-core of certain set(s) was used as an indicator of the significance of that paper, and of the scientific output of its author(s), of their scientific institution(s), etc. An analogous procedure was used to assess the contribution of an individual to the scientific output of his/her scientific institution, branch of science, etc.  相似文献   

17.
This paper introduces a new impact indicator for the research effort of a university, nh3. The number of documents or the number of citations obtained by an institution are used frequently in international ranking of institutions. However, these are very dependent on the size and this is inducing mergers with the apparent sole goal of improving the research ranking. The alternative is to use the ratio of the two measures, the mean citation rate, that is size independent but it has been shown to fluctuate along the time as a consequence of its dependence on a very small number of documents with an extremely good citation performance. In the last few years, the popularity of the Hirsch index as an indicator of the research performance of individual researchers led to its application to journals and institutions. However, the original aim of this h index of giving a mixed measure of the number of documents published and their impact as measured by the citations collected along the time is totally undesirable for institutions as the overall size may be considered irrelevant for the impact evaluation of research. Furthermore, the h index when applied to institutions tends to retain a very small number of documents making all other research production irrelevant for this indicator. The nh3 index proposed here is designed to measure solely the impact of research in a way that is independent of the size of the institution and is made relatively stable by making a 20-year estimate of the citations of the documents produced in a single year.  相似文献   

18.
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   

19.
《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   

20.
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   

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