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Duality is an important topic in informetrics, especially in connection with the classical informetric laws. Yet this concept is less studied in information retrieval. It deals with the unification or symmetry between queries and documents, search formulation versus indexing, and relevant versus retrieved documents. These ideas are elaborated in this note and the connection with the hypergeometric distribution is highlighted.

Generally speaking, the three‐year synchronous impact factor is larger than the two‐year one. This follows from theoretical models derived from observations based on ISIÒs database. In this article we present an exception to this general rule, based on data from the Chinese Science Citation Database (CSCD). In 1998 42% of this databaseÒs source journals did not follow the expected trend. As a possible explanation we note that, contrary to intuition, in the CSCD the changes in the number of both publications and citations are largely independent. It is, however, not ruled out that the observed discrepancies are nothing but statistical fluctuations of the basic publication‐citation model.

Ajiferuke showed that observed author distributions can best be described by a shifted inverse Gaussian‐Poisson distribution. Yet, in the framework of a model to explain observed fractional distributions of authors it is important to know whether a simple one‐parameter distribution such as a geometric or a truncated Poisson can adequately describe observed author distributions, at least in those fields where the single author is still dominant. In this article it is shown that for the field of information science this is indeed the case.

Sir, why am I not cited or why are multi‐authored papers more cited than others?

A research model is proposed to prove or disprove the dependence of a field list of internationally visible journals on the initial set. Applications of the experiment are outlined. A conjecture is formulated concerning the validity of isi's impact factors.

The purpose of this paper is to extend the h-index framework to the case that articles are counted fractionally.

Three restrictions related to the standard h-index are explained: as the standard h-index is a natural number it is a rather coarse indicator; if a scientist has published a relatively small number of publications then the h-index is completely determined by the number of publications; the standard h-index cannot be applied if publications are counted fractionally, or when magnitude values smaller than one occur.

We recall solutions we proposed in earlier publications regarding the first two problems (the use of the interpolated h-index and of the pseudo h-index) and add a new proposal to solve the third problem. The relation between the recently introduced window/field-normalized h-type index (hwf-index) and the interpolated h-index is described. A real-world example proves the feasibility of this proposal.

Colleagues have shown that the h-index and its variations have fatal flaws and hence should never be used. Yet, not everyone agrees with this opinion.

Assuming that the h-index still has some value, this paper introduces a refinement of the interpolated h-index, called the generalized interpolated h-index. In this way the h-index framework is extended to incorporate, for instance, the case that fractional counting for publications and citations is applied.

The paper aims to propose the use of spline functions for the description and visualization of discrete informetric data.

Interpolating cubic splines: are interpolating functions (they pass through the given data points); are cubic, i.e. are polynomials of third degree; have first and second derivatives in the data points, implying that they connect data points in a smooth way; satisfy a best‐approximation property which tends to reduce curvature. These properties are illustrated in the paper using real citation data.

The paper reveals that calculating splines yields a differentiable function that still captures small but real changes. It offers a middle way between connecting discrete data by line segments and providing an overall best‐fitting curve.

The major disadvantage of the use of splines is that accurate data are essential.

Spline functions can be used for illustrative as well as modelling purposes.

Splines have hardly ever been used or studied in the information sciences.

Aims to review Fairthorne's classic article “Empirical hyperbolic distributions (Bradford‐Zipf‐Mandelbrot) for bibliometric description and prediction” (Journal of Documentation, Vol. 25, pp. 319‐343, 1969), as part of a series marking the Journal of Documentation's 60th anniversary.

Analysis of article content, qualitative evaluation of its subsequent impact, citation analysis, and diffusion analysis.

The content, further developments and influence on the field of informetrics of this landmark paper are explained.

A review is given of the contents of Fairthorne's original article and its influence on the field of informetrics. Its transdisciplinary reception is measured through a diffusion analysis.

The purpose of this paper is to clarify earlier work on journal diffusion metrics. Classical journal indicators such as the Garfield impact factor do not measure the breadth of influence across the literature of a particular journal title. As a new approach to measuring research influence, the study complements these existing metrics with a series of formally described diffusion factors.

Using a publication‐citation matrix as an organising construct, the paper develops formal descriptions of two forms of diffusion metric: “relative diffusion factors” and “journal diffusion factors” in both their synchronous and diachronous forms. It also provides worked examples for selected library and information science and economics journals, plus a sample of health information papers to illustrate their construction and use.

Diffusion factors capture different aspects of the citation reception process than existing bibliometric measures. The paper shows that diffusion factors can be applied at the whole journal level or for sets of articles and that they provide a richer evidence base for citation analyses than traditional measures alone.

The focus of this paper is on clarifying the concepts underlying diffusion factors and there is unlimited scope for further work to apply these metrics to much larger and more comprehensive data sets than has been attempted here.

These new tools extend the range of tools available for bibliometric, and possibly webometric, analysis. Diffusion factors might find particular application in studies where the research questions focus on the dynamic aspects of innovation and knowledge transfer.

This paper will be of interest to those with theoretical interests in informetric distributions as well as those interested in science policy and innovation studies.

The yield period of a journal is defined as the time needed to accumulate the same number of citations as the number of references included during the period of study. Yield sequences are proposed as journal attractivity indicators describing dynamic characteristics of a journal. This paper aims to investigate their use.

As a case study the yield sequences of the journals Nature and Science from 1955 onward are determined. Similarities and dissimilarities between these sequences are discussed and factors affecting yield periods are determined.

The study finds that yield sequences make dynamic aspects of a journal visible, as reflected through citations. Exceptional circumstances (here the publication of Laemmli's paper in 1970 in the journal Nature) become clearly visible. The average number of references per article, the citation distribution and the size of the database used to collect citations are factors influencing yield sequences.

A new dynamic indicator for the study of journals is introduced.