Download e-book for kindle: Power Laws in the Information Production Process: Lotkaian by Leo Egghe

By Leo Egghe

ISBN-10: 0120887533

ISBN-13: 9780120887538

ISBN-10: 1423709284

ISBN-13: 9781423709282

This e-book describes informetric effects from the perspective of Lotkaian size-frequency services, i.e. features which are reducing energy legislation. factors and examples of this version are given exhibiting that it's the most vital regularity among different attainable types. This concept is then built within the framework of IPPs (Information creation approaches) hereby additionally indicating its relation with e.g. the legislation of Zipf.Applications are given within the following fields: third-dimensional informetrics (positive reinforcement and Type/Token-Taken informetrics), focus conception (including the outline of Lorenz curves and focus measures in Lotkaian informetrics), fractal complexity idea (Lotkaian informetrics as self-similar fractals), Lotkaian informetrics during which goods may have a number of assets (where fractional size-frequency capabilities are constructed), the idea of first-citation distributions and the N-fold Cartesian made from IPPs (describing frequency capabilities for N-grams and N-word phrases).In the Appendix, tools are given to figure out the parameters within the legislations of Lotka, according to a suite of discrete facts. The publication explains various informetric regularities, merely in keeping with a reducing strength legislations as size-frequency functionality, i.e. Lotka's legislations. It revives the historic formula of Alfred Lotka of 1926 and exhibits the facility of this strength legislation, either in classical elements of informetrics (libraries, bibliographies) in addition to in 'new' functions corresponding to social networks (citation or collaboration networks and the Internet).

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Additional resources for Power Laws in the Information Production Process: Lotkaian Informetrics (Library and Information Science)

Sample text

Lotka (1926) used the latter method (senior author count), hence treating papers as single authored and hence also circumventing the problem of multiple authorship. Potter (1981) thinks to have an explanation for Lotka's choice of counting only senior authors. First, in Lotka's Chemical Abstracts data, only the first four authors are indexed. However, the second, third and fourth author only receive a "see" reference to the first author and from this it is a lot of work to compile author productivity data based on total counts.

41) N(t0) is the density of sources that are (at t0) x time units old. 42) represents the overall age density. 37) twice: P(X) = C a 2 2 implies -j2. 43) yields (replacing the dummy variable x' by the dummy variable p ' ) 1 ' F(p)= K ' J o ina 2 p ' ' r^Avi^^ Jo I n a 2 [ c 2 p' F(p) = / ; ^ - c ^ p ^ i d p ' (L46) being the cumulative distribution function of sources with less than or equal to p items. Hence, the size-frequency distribution f(p) is nothing else than F'(p). Hence f( p ) = p . 48) will be basic for the fractal description of Lotkaian IPPs as self-similar fractals (see Chapter V).

So the number of sources with n items is proportional to a decreasing power law. ) and in Auerbach's Geschichtstafeln der Physik of 1910. 888 for the Chemical Abstracts data. 7). 055 for Auerbach's data, both very close to Lotka's original findings! Rousseau used his program to fit Lotka's law, which is available at Rousseau and Rousseau (2000), see also the Appendix III. It is underlined in Yablonsky (1985), Haitun (1982b), Ivancheva (2001), Huber (2001) that statistical fitting of a power law often is impossible, certainly for low a .

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Power Laws in the Information Production Process: Lotkaian Informetrics (Library and Information Science) by Leo Egghe


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