Dynamics of Democratic Elections explores modeling approaches to democratic elections and opinion dynamics at the intersection of mathematics, political science, and computational modeling. The book focuses on relatively simple models, their analysis, and how they perform in real-world applications. In order to make the book easy to navigate, the material is divided into three major parts concerning ‘The Voter Model’, ‘Nonlinear Election Models’, and ‘Game Theoretical Models’. Although the material is unashamedly mathematical, the concepts are discussed in a way that should be accessible to anyone with a reasonably strong quantitative background and should prove interesting to a broad audience beyond mathematicians.
Features
· Suitable for graduate students and researchers (mathematicians, physicists, social and political scientists with a strong theoretical background)
· Step-by-step data preparation and analysis
· Abundant exercises
· Numerous color illustrations.
Foreword Preface Section I The Voter Model and its extensions Chapter 1 Warm up: Votes per candidate Chapter 2 The voter model Chapter 3 The zealot Model Chapter 4 The Voter Model with Party Dynamics Section II Nonlinear election models Chapter 5 Elections and the Potts model Chapter 6 Reinforcement Model Chapter 7 Unifying ground of the Potts and the Voter model Chapter 8 Hierarchical models Section III Rational voting - Game theoretical models Chapter 9 Spatial valence model Chapter 10 Voting paradox Appendix A Dynamical systems in a nutshell Appendix B Stochastic models in a nutshell Appendix C Voter Model with Party Dynamics – details Appendix D Appendix: Tables for chapter 7 Bibliography Appendix E Data sources
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