The influence of self-citation corrections on Egghe's g index

The g index was introduced by Leo Egghe as an improvement of Hirsch's index h for measuring the overall citation record of a set of articles. It better takes into account the highly skewed frequency distribution of citations than the h index. I propose to sharpen this g index by excluding the self-citations. I have worked out nine practical cases in physics and compare the h and g values with and without self-citations. As expected, the g index characterizes the data set better than the h index. The influence of the self-citations appears to be more significant for the g index than for the h index.Comment: 9 pages, 2 figures, submitted to Scientometric

Bounds and Inequalities Relating h-Index, g-Index, e-Index and Generalized Impact Factor

Finding relationships among different indices such as h-index, g-index, e-index, and generalized impact factor is a challenging task. In this paper, we describe some bounds and inequalities relating h-index, g-index, e-index, and generalized impact factor. We derive the bounds and inequalities relating these indexing parameters from their basic definitions and without assuming any continuous model to be followed by any of them.Comment: 17 pages, 6 figures, 5 table

Statistical inference on the h-index with an application to top-scientist performance

Despite the huge amount of literature on h-index, few papers have been devoted to the statistical analysis of h-index when a probabilistic distribution is assumed for citation counts. The present contribution relies on showing the available inferential techniques, by providing the details for proper point and set estimation of the theoretical h-index. Moreover, some issues on simultaneous inference - aimed to produce suitable scholar comparisons - are carried out. Finally, the analysis of the citation dataset for the Nobel Laureates (in the last five years) and for the Fields medallists (from 2002 onward) is proposed.Comment: 14 pages, 3 table

Citation Statistics from 110 Years of Physical Review

Publicly available data reveal long-term systematic features about citation statistics and how papers are referenced. The data also tell fascinating citation histories of individual articles.Comment: This is esssentially identical to the article that appeared in the June 2005 issue of Physics Toda

An index to quantify an individual's scientific research output that takes into account the effect of multiple coauthorship

I propose the index $\hbar$ ("hbar"), defined as the number of papers of an individual that have citation count larger than or equal to the $\hbar$ of all coauthors of each paper, as a useful index to characterize the scientific output of a researcher that takes into account the effect of multiple coauthorship. The bar is higher for $\hbar$.Comment: A few minor changes from v1. To be published in Scientometric

Diffusion of scientific credits and the ranking of scientists

Recently, the abundance of digital data enabled the implementation of graph based ranking algorithms that provide system level analysis for ranking publications and authors. Here we take advantage of the entire Physical Review publication archive (1893-2006) to construct authors' networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network we define a ranking method based on a diffusion algorithm that mimics the spreading of scientific credits on the network. We compare the results obtained with our algorithm with those obtained by local measures such as the citation count and provide a statistical analysis of the assignment of major career awards in the area of Physics. A web site where the algorithm is made available to perform customized rank analysis can be found at the address http://www.physauthorsrank.orgComment: Revised version. 11 pages, 10 figures, 1 table. The portal to compute the rankings of scientists is at http://www.physauthorsrank.or

Proposals for evaluating the regularity of a scientist'sresearch output

Evaluating the career of individual scientists according to their scientific output is a common bibliometric problem. Two aspects are classically taken into account: overall productivity and overall diffusion/impact, which can be measured by a plethora of indicators that consider publications and/or citations separately or synthesise these two quantities into a single number (e.g. h-index). A secondary aspect, which is sometimes mentioned in the rules of competitive examinations for research position/promotion, is time regularity of one researcher's scientific output. Despite the fact that it is sometimes invoked, a clear definition of regularity is still lacking. We define it as the ability of generating an active and stable research output over time, in terms of both publications/ quantity and citations/diffusion. The goal of this paper is introducing three analysis tools to perform qualitative/quantitative evaluations on the regularity of one scientist's output in a simple and organic way. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and (3) a simplified procedure for comparing the research output of several scientists according to their publication and citation temporal distributions (Borda's ranking). Description of these tools is supported by several examples

Rescaling citations of publications in physics

We analyze the citation distributions of all papers published in Physical Review journals between 1985 and 2009. The average number of citations received by papers published in a given year and in a given field is computed. Large variations are found, showing that it is not fair to compare citation numbers across fields and years. However, when a rescaling procedure by the average is used, it is possible to compare impartially articles across years and fields. We make the rescaling factors available for use by the readers. We also show that rescaling citation numbers by the number of publication authors has strong effects and should therefore be taken into account when assessing the bibliometric performance of researchers.Comment: 8 pages, 10 figures, 1 tabl

The e-Index, Complementing the h-Index for Excess Citations

BACKGROUND: The h-index has already been used by major citation databases to evaluate the academic performance of individual scientists. Although effective and simple, the h-index suffers from some drawbacks that limit its use in accurately and fairly comparing the scientific output of different researchers. These drawbacks include information loss and low resolution: the former refers to the fact that in addition to h(2) citations for papers in the h-core, excess citations are completely ignored, whereas the latter means that it is common for a group of researchers to have an identical h-index. METHODOLOGY/PRINCIPAL FINDINGS: To solve these problems, I here propose the e-index, where e(2) represents the ignored excess citations, in addition to the h(2) citations for h-core papers. Citation information can be completely depicted by using the h-index together with the e-index, which are independent of each other. Some other h-type indices, such as a and R, are h-dependent, have information redundancy with h, and therefore, when used together with h, mask the real differences in excess citations of different researchers. CONCLUSIONS/SIGNIFICANCE: Although simple, the e-index is a necessary h-index complement, especially for evaluating highly cited scientists or for precisely comparing the scientific output of a group of scientists having an identical h-index