Overview
- Edited and Authored by leading researchers in the field
- First interdisciplinary treatment of this topic and the interface of information and systems sciences, scientometrics and social complex networks
- Addresses a wider academic and professional audience
- Includes supplementary material: sn.pub/extras
Part of the book series: Understanding Complex Systems (UCS)
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Table of contents (8 chapters)
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Front Matter
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Exemplary Model Types
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Front Matter
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Exemplary Model Applications
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Front Matter
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Exemplary Model Applications
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Outlook
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Front Matter
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Back Matter
Keywords
About this book
Models of Science Dynamics aims to capture the structure and evolution of science, the emerging arena in which scholars, science and the communication of science become themselves the basic objects of research. In order to capture the essence of phenomena as diverse as the structure of co-authorship networks or the evolution of citation diffusion patterns, such models can be represented by conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, or computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive study of the topic. This volume fills this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented cover stochastic and statistical models, system-dynamics approaches, agent-based simulations, population-dynamics models, and complex-network models. The book comprises an introduction and a foundational chapter that defines and operationalizes terminology used in the study of science, as well as a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of remaining challenges for future science models and their relevance for science and science policy.
Reviews
From the reviews:
“The book is a comprehensive review of the mathematical models of science from its origins. … each chapter has ‘checkpoints’, i.e., a box or a table presenting either a list of relevant questions together with short answers or a summary of the key-points discussed. This particular structure makes the book especially suited for graduate students and scholars … . experts will surely appreciate the richness and depth of the cited literature, for the first time so well organized into a single book.” (Stefano Balietti, Journal of Artificial Societies and Social Simulation, Vol. 15 (3), 2012)
Editors and Affiliations
Bibliographic Information
Book Title: Models of Science Dynamics
Book Subtitle: Encounters Between Complexity Theory and Information Sciences
Editors: Andrea Scharnhorst, Katy Börner, Peter Besselaar
Series Title: Understanding Complex Systems
DOI: https://doi.org/10.1007/978-3-642-23068-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Physics and Astronomy, Physics and Astronomy (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2012
Hardcover ISBN: 978-3-642-23067-7Published: 23 January 2012
Softcover ISBN: 978-3-642-44884-3Published: 22 February 2014
eBook ISBN: 978-3-642-23068-4Published: 24 January 2012
Series ISSN: 1860-0832
Series E-ISSN: 1860-0840
Edition Number: 1
Number of Pages: XXX, 270
Topics: Methodology of the Social Sciences, Data-driven Science, Modeling and Theory Building, Information Systems Applications (incl. Internet), Complexity