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- Author or Editor: Quentin Burrell x
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Abstract
Certain similarities between the types of data reported in retrospective citation analyses and lifetime/survival/reliability models are noted. Graphical techniques much used in reliability analyses are exploited to throw further light on observed citation age distributions and these are then compared and contrasted with previously reported studies. These simple techniques allow systematic departures of empirical data from assumed theoretical models to be highlighted and the models to be compared.
Abstract
Hirsch’s h-index gives a single number that in some sense summarizes an author’s research output and its impact. Since an individual author’s h-index will be time-dependent, we propose instead the h-rate which, according to theory, is (almost) constant. We re-analyse a previously published data set (Liang, 2006) which, although not of the precise form to properly test our model, reveals that in many cases we do not have a constant h-rate. On the other hand this then suggests ways in which deeper scientometric investigations could be carried out. This work should be viewed as complementary to that of Liang (2006).
Abstract
It is a well-known empirical fact that when informetric processes are observed over an extending period of time, the entire shape of the distribution changes. In particular, it has been shown that concentration aspects change. In this paper the recently introduced co-concentration coefficient (C-CC) is investigated via simple stochastic models of informetric processes to investigate its time-dependence. It is shown that it is important to distinguish between situations where the zero-producers can be counted and those where they cannot. A previously published data set is used to illustrate how the empirical C-CC develops in time and the general features are compared with those derived from the theoretical model.
Abstract
The stochastic model proposed recently by the author to describe the citation process in the presence of obsolescence is further investigated to illustrate the nth-citation distribution and the distribution of the total number of citations. The particular case where the latent rate has a gamma distribution is analysed in detail and is shown to be able to agree well with empirical data.
Abstract
In recent issues of the ISSI Newsletter, Egghe [2006a] proposed the g-index and Kosmulski [2006] the h(2)-index, both claimed to be improvements on the original h-index proposed by Hirsch [2005]. The aim of this paper is to investigate the inter-relationships between these measures and also their time dependence using the stochastic publication/citation model proposed by Burrell [1992, 2007a]. We also make some tentative suggestions regarding the relative merits of these three proposed measures.
Summary
There is a well-established literature on the use of concentration measures in informetrics. However, these works have usually been devoted to measures of concentration within a productivity distribution. In a pair of recent papers the author introduced two new measures, both based on the Gini ratio, for measuring the similarity of concentration of productivity between two different informetric distributions. The first of these was derived from Dagum's notion of relative economic affluence; the second - in some ways analogous to the correlation coefficient - is completely new. The purpose of this study is to develop a purely empirical approach to comparative studies of concentration between informetric data sets using both within and between measures thereby greatly extending the original study which considered just two data sets for purposes of illustration of the methods of calculation of the measures.
