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Introduction Today, the h index (Hirsch 2005 ) is a widely used measure of scientific performance: “The automatic calculation of h -indices has even become a built-in feature of major bibliographic databases such as Web of
.g. a department, a journal, a field of enquiry) the h index is the largest number of papers with ≥ h citations each. Thus, a scientist with an h index of 10 has ten papers with at least ten citations each but not 11 papers with at least 11
Abstract
This paper studies four different h-index sequences (different in publication periods and/or citation periods). Lotkaian models for these h-index sequences are presented by mutual comparison of one sequence with another one. We also give graphs of these h-sequences for this author on which a discussion is presented. The same is done for the g-index and the R-index.
Abstract
Over the last years the h-index has gained popularity as a measure for comparing the impact of scientists. We investigate if ranking according to the h-index is stable with respect to (i) different choices of citation databases, (ii) normalizing citation counts by the number of authors or by removing self-citations, (iii) small amounts of noise created by randomly removing citations or publications and (iv) small changes in the definition of the index. In experiments for 5,283 computer scientists and 1,354 physicists we show that although the ranking of the h-index is stable under most of these changes, it is unstable when different databases are used. Therefore, comparisons based on the h-index should only be trusted when the rankings of multiple citation databases agree.
evaluate scientific output of a researcher. Hirsch ( 2005 ) proposed the h -index to quantify an individual scientific research output. The h -index has gained considerable acceptance as a measure of individual research achievement. It is
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In this paper we examine the applicability of the concept of h-index to topics, where a topic has index h, if there are h publications that received at least h citations and the rest of the publications on the topic received at most h citations. We discuss methodological issues related to the computation of h-index of topics (denoted h-b index by BANKS [2006]). Data collection for computing the h-b index is much more complex than computing the index for authors, research groups and/or journals, and has several limitations. We demonstrate the methods on a number of informetric topics, among them the h-index.
Introduction Since the publication of Hirsch's paper in 2005 that proposes what is now called the ‘ h -index’ as a way to quantify an individual's research performance, many other metrics have been developed and promoted as
Abstract
The h-index has captured the imagination of scientometricians and bibliometricians to such an extent that one can now divide the history of the subject virtually into a pre-Hirsch and a post-Hirsch period. Beyond its academic value, it is now used as a tool for research assessment of individuals, research faculties and institutions and even for comparing performance of journals and countries. Since its introduction, many Hirsch-type variants have been proposed to overcome perceived limitations of the original index. In this paper, using ideas from mathematical modeling, another mock h-index is proposed which may complement the h-index and give it better resolving power.
Abstract
Based on two large data samples from ISI databases, the author evaluated the Hirsch model, the Egghe-Rousseau model, and the Glänzel-Schubert model of the h-index. The results support the Glänzel-Schubert model as a better estimation of the h-index at both journal and institution levels. If h c , h p and h pc stand for the Hirsch estimation, Egghe-Rousseau estimation, and Glänzel-Schubert estimation, respectively, then an inequality h p < h ∼ h pc < h c holds in most cases.
Abstract
The h-index and Eigenfactor TM values of top and specialized scientific/engineering journals are tabulated and combined to provide a simple graphical representation of the journals. The information may be tailored to specific uses by respective stakeholders to aid decision making processes with regards to scholarly research and scientific journal publications.
