Authors:
- Presents a self-contained introduction to conflict modeling
- Provides novel concepts which are broadly applicable
- Contains supplementary material, e.g. code and data sets
- Written by experts in the field
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Mathematical Methods (BRIEFSMATHMETH)
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Table of contents (3 chapters)
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Front Matter
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Back Matter
About this book
The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years. The target audience primarily comprises researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
Authors and Affiliations
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School of Geographical Sciences Department of Mathematics, The University of Bristol, Bristol, United Kingdom
Andrew Zammit-Mangion
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New York, USA
Michael Dewar
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Automatic Control & Systems Engineering, The University of Sheffield, Sheffield, United Kingdom
Visakan Kadirkamanathan
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GIGA German Institute of Global and Area, Hamburg, Germany
Anaïd Flesken
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School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
Guido Sanguinetti
Bibliographic Information
Book Title: Modeling Conflict Dynamics with Spatio-temporal Data
Authors: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Flesken, Guido Sanguinetti
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-3-319-01038-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2013
Softcover ISBN: 978-3-319-01037-3Published: 11 October 2013
eBook ISBN: 978-3-319-01038-0Published: 30 September 2013
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: VIII, 74
Number of Illustrations: 12 b/w illustrations, 1 illustrations in colour
Topics: Data-driven Science, Modeling and Theory Building, Mathematics in the Humanities and Social Sciences, Complexity, Probability Theory and Stochastic Processes, Signal, Image and Speech Processing