I propose to sharpen the index h, proposed by Hirsch as a useful index to characterize the scientific output of a researcher, by excluding the self-citations. Performing a self-experiment and also analyzing two anonymous data sets, it is shown that self-citations can significantly reduce the $h$ index in contrast to Hirsch's expectations. This result is confirmed by an analysis of 13 further data sets.
The h-index has been shown to increase in many cases mostly because of citations to rather old publications. This inertia can be circumvented by restricting the evaluation to a citation time window. Here I report results of an empirical study analyzing the evolution of the thus defined timed h-index in dependence on the length of the citation time window.
A Case Study of the Modified Hirsch Index hm Accounting for Multiple Co-authors
J. E.赫希（2005年）引入了h指数，通过科学家论文的最大数量h来量化个人的科学研究成果，这些论文至少被引用了h次。这个所谓的赫希指数可以很容易地修改，以考虑到多个合著者，通过计算论文分数根据（倒数）的作者人数。我列举了26个物理学家的经验案例来说明这种修正的效果。虽然原始的和修改后的赫希指数之间的相关性是相对较强的，数据集的安排是显着不同的，这取决于它们是否被放入根据原始或修改后的指数的值的顺序。
A popular measure for citation inequalities of individual scientists has been the Hirsch index ($h$). If for any scientist the number $n_c$ of citations is plotted against the serial number $n_p$ of the paper having those many citations (when the papers are ordered from highest cited to lowest) then $h$ corresponds to the nearest lower integer value of $n_p$ below the fixed point of the non-linear citation function (or given by $n_c = h = n_p$ if both $n_p$ and $n_c$ are dense set of integers near the $h$ value). The same index can be estimated (from $h=s=n_{s}$) for the avalanche or cluster o…
Utilizing the Hirsch index h and some of its variants for an exploratory factor analysis we discuss whether one of the most important Hirsch-type indices, namely the g-index comprises information about not only the size of the productive core but also the impact of the papers in the core. We also study the effect of logarithmic and square-root transformation of the data utilized in the factor analysis. To demonstrate our approach we use a real data example analysing the citation records of 26 physicists compiled from the Web of Science.
A few new indices to characterize the scientific output of scientists are defined in the paper. These indices are compared with -index and its alternative indices using some proven assertions. The gd-indices are introduced as extensions of the g-index to define H-index as an improvement of the h-index. Numerous computational results which are conducted indicate the good behaviour of defined indices to evaluate the scientific impact of scientists. There exist very good approximations between some pairs of all considered indices in the sense that related ratios are often very close to 1.
The generalized $H(n)$ Hirsch index of order $n$ has been recently introduced and shown to interpolate between the degree and the $K$-core centrality in networks. We provide a detailed analytical characterization of the properties of sets of nodes having the same $H(n)$, within the annealed network approximation. The connection between the Hirsch indices and the degree is highlighted. Numerical tests in synthetic uncorrelated networks and real-world correlated ones validate the findings. We also test the use of the Hirsch index for the identification of influential spreaders in networks, findi…
In this paper we present "citation success index", a metric for comparing the citation capacity of pairs of journals. Citation success index is the probability that a random paper in one journal has more citations than a random paper in another journal (50% means the two journals do equally well). Unlike the journal impact factor (IF), the citation success index depends on the broadness and the shape of citation distributions. Also, it is insensitive to sporadic highly-cited papers that skew the IF. Nevertheless, we show, based on 16,000 journals containing ~2.4 million articles, that the cita…
A Comparison between the China Scientific and Technical Papers and Citations Database and the Science Citation Index in terms of journal hierarchies and inter-journal citation relations
Does it Matter Which Citation Tool is Used to Compare the h-index of a Group of Highly Cited Researchers?
由引文索引（Scopus，Google Scholar和Web of Science）检索的h指数用于衡量科学家的科学表现和研究影响力研究，基于科学家的出版物和引文数量。它也很容易获得，可用于科学家的业绩衡量和招聘决定。本研究的目的是调查这三个引文数据库，即Scopus，Google Scholar和Web of Science基于一组高被引研究人员（诺贝尔奖获得者科学家）的h指数的输出和结果之间的差异。本研究采立意抽样方法收集资料。结果表明，Scopus、Google scholar和Web of Science 3个数据库的h指数存在显著性差异，其中Google scholar h指数大于其他2个数据库的h指数。研究还表明，基于Google Scholar和Scopus的h指数之间存在显著的正相关关系。Scopus、Google Scholar和Web of Science的引文索引对科学家h指数的评价有一定的参考价值，但也存在一定的局限性。
随着绝大多数的科学论文现在可以在网上，本文介绍了网络是如何让物理学家和信息提供商更准确地衡量这些论文及其作者的影响。提供了引文分析的历史背景、影响因子、新的引文数据源（例如，Google Scholar、Scopus、NASA的Astrophysics Data System Abstract Service、MathSciNet、ScienceDirect、ScienceScholar、Scitation/SPIN和SPIRES-HEP），以及h-index、g-index和a-index。
We introduce a new centrality index for bipartite network of papers and authors that we call $K$-index. The $K$-index grows with the citation performance of the papers that cite a given researcher and can seen as a measure of scientific social recognition. Indeed, the $K$-index measures the number of hubs, defined in a self-consistent way in the bipartite network, that cites a given author. We show that the $K$-index can be computed by simple inspection of the Web of Science platform and presents several advantages over other centrality indexes, in particular Hirsch $h$-index. The $K$-index is…
The $K$-index is an easily computable centrality index in complex networks, such as a scientific citations network. A researcher has a $K$-index equal to $K$ if he or she is cited by $K$ articles that have at least $K$ citations. The $K$-index has several advantages over Hirsh's $h$-index and, in previous studies, has shown better correlation with Nobel prizes than any other index given by the {\em Web of Science}, including the $h$-index. It is plausible that researchers who are the most connected to other scientifically well-connected researchers are the most likely to be doing important wor…
We present a novel algorithm and validation method for disambiguating author names in very large bibliographic data sets and apply it to the full Web of Science (WoS) citation index. Our algorithm relies only upon the author and citation graphs available for the whole period covered by the WoS. A pair-wise publication similarity metric, which is based on common co-authors, self-citations, shared references and citations, is established to perform a two-step agglomerative clustering that first connects individual papers and then merges similar clusters. This parameterized model is optimized usi…
In this work, we study the correlation between interdisciplinarity of papers within physical sciences and their citations by using meta data of articles published in American Physical Society's Physical Review journals between 1985 to 2012. We use the Weitzman diversity index to measure the diversity of papers and authors, exploiting the hierarchical structure of PACS (Physics and Astronomy Classification Scheme) codes. We find that the fraction of authors with high diversity is increasing with time, where as the fraction of least diversity are decreasing, and moderate diversity authors have h…
Evaluating the performance of researchers and measuring the impact of papers written by scientists is the main objective of citation analysis. Various indices and metrics have been proposed for this. In this paper, we propose a new citation index CITEX, which gives normalized scores to authors and papers to determine their rankings. To the best of our knowledge, this is the first citation index which simultaneously assigns scores to both authors and papers. Using these scores, we can get an objective measure of the reputation of an author and the impact of a paper. We model this problem as an …
The Hirsch's $h$-index is perhaps the most popular citation-based measure of the scientific excellence. In 2013 G. Ionescu and B. Chopard proposed an agent-based model for this index to describe a publications and citations generation process in an abstract scientific community. With such an approach one can simulate a single scientist's activity, and by extension investigate the whole community of researchers. Even though this approach predicts quite well the $h$-index from bibliometric data, only a solution based on simulations was given. In this paper, we complete their results with exact, …
Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with a growing body of literature focused on predicting the number of citations obtained by any given publication. The effectiveness of such predictions, however, is fundamentally limited by the power-law distribution of citations, whereby publications with few citations are extremely common and publications with many citations are relatively rare. Given this limitation, in this work we instead address a related question ask…
A researcher collaborating with many groups will normally have more papers (and thus higher citations and $h$-index) than a researcher spending all his/her time working alone or in a small group. While analyzing an author's research merit, it is therefore not enough to consider only the collective impact of the published papers, it is also necessary to quantify his/her share in the impact. For this quantification, here I propose the $I$-index which is defined as an author's percentage share in the total citations that his/her papers have attracted. It is argued that this $I$-index does not dir…
