Literatur zur Informationserschließung
Diese Datenbank enthält über 40.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft
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1Bensman, S.J. ; Smolinsky, L.J.: Lotka's inverse square law of scientific productivity : its methods and statistics.
In: Journal of the Association for Information Science and Technology. 68(2017) no.7, S.17861791.
(Brief communication)
Abstract: This brief communication analyzes the statistics and methods Lotka used to derive his inverse square law of scientific productivity from the standpoint of modern theory. It finds that he violated the norms of this theory by extremely truncating his data on the right. It also proves that Lotka himself played an important role in establishing the commonly used method of identifying powerlaw behavior by the R2 fit to a regression line on a loglog plot that modern theory considers unreliable by basing the derivation of his law on this very method.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23785/full.
Themenfeld: Informetrie
Objekt: LotkaGesetz

2Smolinsky, L.J.: Discrete power law with exponential cutoff and Lotka's law.
In: Journal of the Association for Information Science and Technology. 68(2017) no.7, S.17921795.
(Brief communication)
Abstract: One of the first bibliometric laws appeared in Alfred J. Lotka's 1926 examination of author productivity in chemistry and physics. The result was a productivity distribution described by a power law. In this paper, Lotka's original data on author productivity in chemistry are reconsidered. We define a discrete power law with exponential cutoff, test Lotka's data, and compare the fit to the discrete power law.
Inhalt: Vgl.: http://onlinelibrary.wiley.com/doi/10.1002/asi.23763/full.
Themenfeld: Informetrie
Objekt: LotkaGesetz

3Egghe, L.: ¬A new short proof of Naranan's theorem, explaining Lotka's law and Zipf's law.
In: Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.25812583.
(Brief communication)
Abstract: Naranan's important theorem, published in Nature in 1970, states that if the number of journals grows exponentially and if the number of articles in each journal grows exponentially (at the same rate for each journal), then the system satisfies Lotka's law and a formula for the Lotka's exponent is given in function of the growth rates of the journals and the articles. This brief communication reproves this result by showing that the system satisfies Zipf's law, which is equivalent with Lotka's law. The proof is short and algebraic and does not use infinitesimal arguments.
Themenfeld: Informetrie
Objekt: NarananTheorem ; ZipfGesetz ; LotkaGesetz

4Rousseau, R.: Informetric laws.
In: Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates. London : Taylor & Francis, 2009. S.xxxx.
Abstract: In this entry we formulate the socalled informetric laws, recall their origin, indicate how it can be shown that they are basically equivalent representations of the same regularity, hint at some explanations, such as successbreedssuccess or preferential attachment, and describe why they are so ubiquitous.
Anmerkung: Vgl.: http://www.tandfonline.com/doi/book/10.1081/EELIS3.
Themenfeld: Informetrie
Objekt: BradfordGesetz ; LotkaGesetz ; ZipfGesetz ; MandelbrotGesetz ; LeimkuhlerGesetz

5Burrell, Q.L.: Extending Lotkaian informetrics.
In: Information processing and management. 44(2008) no.5, S.17941807.
Abstract: The continuous version of the Lotka distribution, more generally referred to outside of informetrics as the Pareto distribution, has long enjoyed a central position in the theoretical development of informetrics despite several reported drawbacks in modelling empirical data distributions, most particularly that the inverse power form seems mainly to be evident only in the upper tails. We give a number of published examples graphically illustrating this shortcoming. In seeking to overcome this, we here draw attention to an intuitively reasonable generalization of the Pareto distribution, namely the Pareto type II distribution, of which we consider two versions. We describe its basic properties and some statistical features together with concentration aspects and argue that, at least in qualitative terms, it is better able to describe many observed informetric phenomena over the full range of the distribution. Suggestions for further investigations, including truncated and timedependent versions, are also given.
Themenfeld: Informetrie
Objekt: LotkaGesetz

6Egghe, L.: ¬A model for the sizefrequency function of coauthor pairs.
In: Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.21332137.
Abstract: Lotka's law was formulated to describe the number of authors with a certain number of publications. Empirical results (Morris & Goldstein, 2007) indicate that Lotka's law is also valid if one counts the number of publications of coauthor pairs. This article gives a simple model proving this to be true, with the same Lotka exponent, if the number of coauthored papers is proportional to the number of papers of the individual coauthors. Under the assumption that this number of coauthored papers is more than proportional to the number of papers of the individual authors (to be explained in the article), we can prove that the sizefrequency function of coauthor pairs is Lotkaian with an exponent that is higher than that of the Lotka function of individual authors, a fact that is confirmed in experimental results.
Themenfeld: Informetrie
Objekt: LotkaGesetz

7Rousseau, R.: On Egghe's construction of Lorenz curves.
In: Journal of the American Society for Information Science and Technology. 58(2007) no.10, S.15511552.
Abstract: Contrary to Burrell's statements, Egghe's theory of continuous concentration does include the construction of a standard Lorenz curve.
Themenfeld: Informetrie
Objekt: ZipfGesetz ; LotkaGesetz

8Morris, S.A. ; Goldstein, M.L.: Manifestation of research teams in journal literature : a growth model of papers, authors, collaboration, coauthorship, weak ties, and Lotka's law.
In: Journal of the American Society for Information Science and Technology. 58(2007) no.12, S.17641782.
Abstract: This article introduces a teambased model of researchers in a specialty and investigates the manifestation of such teams in a specialty's literature. The proposed qualitative behavioral model, with its mathematical expression as a growth model, is significant because it simultaneously describes the two phenomena of collaboration and author productivity (Lotka's law) in a specialty. The model is nested: A team process models the creation of research teams and the successbreedssuccess process of their production of articles, while at a lower level the productivity of authors within teams is also modeled as a successbreedssuccess process. Interteam collaboration (weak ties) is modeled as random events. This simple growth model is shown to faithfully mimic six network metrics of bipartite articleauthor networks. The model is demonstrated on three example article collections from specialties that have a wide range of degree of collaboration: (a) a distance education collection with low collaboration degree, (b) a complex networks collection with typical collaboration degree, and (c) an atrial ablation collection with heavy collaboration degree.
Themenfeld: Informetrie
Objekt: LotkaGesetz

9Egghe, L.: Relations between the continuous and the discrete Lotka power function.
In: Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.664668.
Abstract: The discrete Lotka power function describes the number of sources (e.g., authors) with n = 1, 2, 3, ... items (e.g., publications). As in econometrics, informetrics theory requires functions of a continuous variable j, replacing the discrete variable n. Now j represents item densities instead of number of items. The continuous Lotka power function describes the density of sources with item density j. The discrete Lotka function one obtains from data, obtained empirically; the continuous Lotka function is the one needed when one wants to apply Lotkaian informetrics, i.e., to determine properties that can be derived from the (continuous) model. It is, hence, important to know the relations between the two models. We show that the exponents of the discrete Lotka function (if not too high, i.e., within limits encountered in practice) and of the continuous Lotka function are approximately the same. This is important to know in applying theoretical results (from the continuous model), derived from practical data.
Themenfeld: Informetrie
Objekt: LotkaGesetz

10Egghe, L.: ¬The power of power laws and an interpretation of Lotkaian informetric systems as selfsimilar fractals.
In: Journal of the American Society for Information Science and Technology. 56(2005) no.7, S.669675.
Abstract: Power laws as defined in 1926 by A. Lotka are increasing in importance because they have been found valid in varied social networks including the Internet. In this article some unique properties of power laws are proven. They are shown to characterize functions with the scalefree property (also called seifsimilarity property) as weIl as functions with the product property. Power laws have other desirable properties that are not shared by exponential laws, as we indicate in this paper. Specifically, Naranan (1970) proves the validity of Lotka's law based on the exponential growth of articles in journals and of the number of journals. His argument is reproduced here and a discretetime argument is also given, yielding the same law as that of Lotka. This argument makes it possible to interpret the information production process as a seifsimilar fractal and show the relation between Lotka's exponent and the (seifsimilar) fractal dimension of the system. Lotkaian informetric systems are seifsimilar fractals, a fact revealed by Mandelbrot (1977) in relation to nature, but is also true for random texts, which exemplify a very special type of informetric system.
Themenfeld: Informetrie
Objekt: LotkaGesetz

11Egghe, L.: Zipfian and Lotkaian continuous concentration theory.
In: Journal of the American Society for Information Science and Technology. 56(2005) no.9, S.935945.
Abstract: In this article concentration (i.e., inequality) aspects of the functions of Zipf and of Lotka are studied. Since both functions are power laws (i.e., they are mathematically the same) it suffices to develop one concentration theory for power laws and apply it twice for the different interpretations of the laws of Zipf and Lotka. After a brief repetition of the functional relationships between Zipf's law and Lotka's law, we prove that Price's law of concentration is equivalent with Zipf's law. A major part of this article is devoted to the development of continuous concentration theory, based an Lorenz curves. The Lorenz curve for power functions is calculated and, based an this, some important concentration measures such as the ones of Gini, Theil, and the variation coefficient. Using Lorenz curves, it is shown that the concentration of a power law increases with its exponent and this result is interpreted in terms of the functions of Zipf and Lotka.
Themenfeld: Informetrie
Objekt: ZipfGesetz ; LotkaGesetz

12Rowlands, I.: Emerald authorship data, Lotka's law and research productivity.
In: Aslib proceedings. 57(2005) no.1, S.510.
Abstract: Purpose  This paper offers a practical insight into the application of Lotka's law of author productivity to the question of how likely it is that an author will return to a particular publisher (rather than make another contribution to a subject literature, which is its usual application). The question of author loyalty, especially repeat visits, is one which is of great interest to publishers. Design/methodology/approach  This paper shows, possibly for the first time, that the author productivity distribution predicted by Lotka's law for subject literatures also holds for publisher aggregates, in this case, all Emerald authors. Findings  The ideas presented here are speculative and programmatic: they raise questions and provide a robust intellectual framework for further research into the determinants of author loyalty, as seen from the publisher side. Practical implications  The implications for commissioning editors and marketing departments in journal publishing houses are that repeat visiting authors are indeed scarce commodities, not necessarily because of barriers put in their way by publishers, but because research production is very asymmetrically skewed in favour of a small productive élite. Originality/value  By analysing survey data it should be possible, within very broad parameters, to identify clusters of say high, medium and low research activity authors. This would provide insight into potential "hot spots" of future publishing intent and, in the case of dense and overworked research areas, early warning as to when to start looking elsewhere for future articles.
Themenfeld: Informetrie
Objekt: LotkaGesetz

13Burrell, Q.L.: Fitting Lotka's law : some cautionary observations on a recent paper by Newby et al. (2003).
In: Journal of the American Society for Information Science and Technology. 55(2004) no.13, S.12091210.
Themenfeld: Informetrie
Objekt: LotkaGesetz

14Huber, J.C.: ¬A new model that generated Lotka's law.
In: Journal of the American Society for Information Science and technology. 53(2002) no.3, S.209219.
Abstract: In this paper, we develop a new model for a process that generates Lotka's Law. We show that four relatively mild assumptions create a process that fits five different informetric distributions: rate of production, career duration, randomness, and Poisson distribution over time, as well as Lotka's Law. By simulation, we obtain good fits to three empirical samples that exhibit the extreme range of the observed parameters. The overall error is 7% or less. An advantage of this model is that the parameters can be linked to observable human factors. That is, the model is not merely descriptive, but also provides insight into the causes of differences between samples. Furthermore, the differences can be tested with powerful statistical tools
Themenfeld: Informetrie
Objekt: LotkaGesetz

15Egghe, L. ; Ravichandra Rao, I.K.: Duality revisited : construction of fractional frequency distributions based on two dual Lotka laws.
In: Journal of the American Society for Information Science and technology. 53(2002) no.10, S.789801.
Abstract: Fractional frequency distributions of, for example, authors with a certain (fractional) number of papers are very irregular and, therefore, not easy to model or to explain. This article gives a first attempt to this by assuming two simple Lotka laws (with exponent 2): one for the number of authors with n papers (total count here) and one for the number of papers with n authors, n E N. Based an an earlier made convolution model of Egghe, interpreted and reworked now for discrete scores, we are able to produce theoretical fractional frequency distributions with only one parameter, which are in very close agreement with the practical ones as found in a large dataset produced earlier by Rao. The article also shows that (irregular) fractional frequency distributions are a consequence of Lotka's law, and are not examples of breakdowns of this famous historical law.
Themenfeld: Informetrie
Objekt: LotkaGesetz

16Burrell, Q.L.: "Ambiguity" ans scientometric measurement : a dissenting view.
In: Journal of the American Society for Information Science and technology. 52(2001) no.12, S.10751080.
Abstract: Abe Bookstein has long been a persuasive advocate of the central role of the classical LotkaBradfordZipf "laws" in bibliometrics and, subsequently, scientometrics and informetrics. In a series of oftenquoted papers (Bookstein, 1977, 1990a, 1990b, 1997), he has sought to demonstrate that "Lotkatype" laws have a unique resilience to various forms of reporting, which leads inevitably and naturally to their observance in empirical informetric data collected under a wide variety of circumstances. A general statement of his position was featured in the recent JASIST Special Topic Issue on Information Science at the Millennium (Bookstein, 2001). We shall argue that there are grounds to dispute some of the logic, the mathematics, and the reality of the development. The contention is on the one hand that Bookstein's development lacks a rigorous mathematical basis, and on the other, that, in general, informetric processes are adequately described within a standard probabilistic framework with stochastic modelling offering the more productive approach.
Themenfeld: Informetrie
Objekt: LotkaGesetz

17Kretschmer, H. ; Rousseau, R.: Author inflation leads to a breakdown of Lotka's law : in and out of context.
In: Journal of the American Society for Information Science and technology. 52(2001) no.8, S.610614.
Abstract: Fractional counting of authors of multiauthored papers has been shown to lead to a breakdown of Lotka's Law despite its robust character under most circumstances. Kretschmer and Rousseau use the normal count method of full credit for each author on two fiveyear bibliographies from each of 13 Dutch physics institutes where high coauthorship is a common occurrence. KolmogorovSmirnov tests were preformed to see if the Lotka distribution fit the data. All bibliographies up to 40 authors fit acceptably; no bibliography with a paper with over 100 authors fits the distribution. The underlying traditional "success breeds success" mechanism assumes new items on a one by one basis, but Egghe's generalized model would still account for the process. It seems unlikely that Lotka's Law will hold in a high coauthorship environment.
Themenfeld: Informetrie
Objekt: LotkaGesetz

18Joshi, A.N. ; Maheshwarappa, B.S.: Studies in scientific productivity : a review of literature.
In: International information communication and education. 15(1996) no.2, S.161176.
Abstract: Refers to the many changes in the research process in the post Second World War period, including the increased involvement of government and industry in establishing R&D laboratories, and by way of grant to universities. Discusses concepts, types, and problems in measuring scientific productivity, reviewing studies since 1926. Examines theoretical developments in relation to the frequency distribution of Lotka's Law of Scientific Productivity. The various studies are mainly noncomparable and inconclusive owing to substantial differences in the analytical methods applied. Poits out the need for methodological standardisation and coordination of research efforts in this area through empirical validation and generalisation of bibliometric models
Themenfeld: Informetrie
Objekt: LotkaGesetz

19Egghe, L.: Special features of the author  publication relationship and a new explanation of Lotka's law based on convolution theory.
In: Journal of the American Society for Information Science. 45(1994) no.6, S.422427.
Themenfeld: Informetrie
Objekt: LotkaGesetz

20Rousseau, R.: ¬A table for estimating the exponent in Lotka's law.
In: Journal of documentation. 49(1993) no.4, S.409412.
Themenfeld: Informetrie
Objekt: LotkaGesetz