信息生产和使用，表征信息计量学分布的努力函数和密度函数：指数信息计量学方法（英文）.pdfVIP

Production and use of information. Characterization of informetric distributions using effort function and density function Exponential informetric process Thierry Lafouge *, Camille Prime-Claverie ´ Laboratoire Ursidoc, Universite Claude Bernard, Lyon1, 43 Boulevard du 11 novembre 1918, 69622 Villeurbanne Cedex, France Received 27 September 2004; accepted 3 March 2005 Abstract Statistical regularities observed in the production or use of information have been studied for a long time. In this article we define an exponential informetric process to formalize these stochastic process. It is defined by combining an effort function with a density function. Without using the powerful results of Price on the cumulative advantages process this characterization clarifies the principle of least effort. Some links between statistical theory of information and some informetric distributions are enhanced. 2005 Elsevier Ltd. All rights reserved. Keywords: Effort function; Exponential process; Entropy 1. Introduction Scientific production is cumulative by nature. If we look from a scientometric point of view and evaluate the number of articles produced by researchers, we know that each new scientific article published is usually built on previous results. In his article, an author quotes the bibliographic references of other work pro- duced earlier (which may be his) in order to validate his work. Furthermore, a known social phenomenon, ‘‘success breeds success’’, will then occur: the (n + 1)th publication will be easier than the preceding one. It will require less effort than the nth publication. This law may prove false for a given p