Modeling the Structure and Dynamics of Science Using Books

Abstract

Prize annually to scholars that have made a distinguished contribution to the field. The first three award recipients were Derek de Solla Price (1981), Robert K. , and Thomas S. Kuhn and their books Little Science, Big Science (Price, 1963), The Sociology of Science The Structure of Scientific Revolutions (Kuhn, 1962) are included in this analysis.Predictive models of science (computational and mathematical) are developed in scientometrics, bibliometrics, system dynamics, physics and mathematics, but also more recently in a new branch of philosophy of science and cognition (Payette, 2012). One of the first predictive models was introduced by Goffman-he used a model originally developed to predict the spread of diseases to describe the spreading of ideas (Goffman & Nevill 1964;Goffman 1966;Harmon 2008). The so-called SIR model orders researchers in three categories: the number researchers 'susceptible' to a new idea but not yet infected with it (S), the number of 'infected' researchers (I), and the number of 'recovered' researchers (R) who lost interest and will not return to the idea. The model presumes that boundaries of scientific fields and/or invisible colleges (Crane, 1972) can be defined. Goffman's work showcases the complex relationship between mathematical, theoretical models and their empirical validation. Using his model, it is possible to define with which possibility a researcher becomes 'infected' with an idea and the predicted growth rate of a new scientific field can be compared with the actual growth rate (Wagner-Döbler, 1999), see review of follow-up studies in (Lucio-Arias & Scharnhorst, 2012)). Case studies also show that it is not easy to validate all processes inscribed in Goffman's model (Burger & Bujdoso, 1985).Goffman's model is only one out of many approaches to conceptualize science. As of today, there exists no unifying framework that would interlink models-neither in terms of co-author communities nor in terms of citation linkages between publications. When (Lucio-Arias & Scharnhorst, 2012) presented a bibliometric study of a set of relevant LIS journals

The impact of J. D. Bernal’s thoughts in the science of science upon China: Implications for today’s quantitative studies of science

“…Nowadays, the analysis of citation networks has been an important tool for understanding science dynamics in quantitative studies of science. In fact, the structure of The social function of science reads like a what-to-be-modeled list (Ginda, Scharnhorst, & Börner, 2016). Examples are organization (The existing organization of research in Britain), scientific practices (The efficiency of scientific research), scientific careers (The training of the scientist) or globalization (International science).…”