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Intro -- Acknowledgements -- Prologue -- Contents -- 1 Introduction: The Digital Society -- 1.1 Living in the Age of "Big Data" -- 1.2 Data Sets Bigger Than the Largest Library -- 1.3 Will a Digital Revolution Solve Our Problems? -- 1.4 Big Data Gold Rush for the Twenty-First Century's Oil -- 1.5 Will Artificial Intelligence Overtake Us? -- 1.6 When Big Data Starts to Steer Our Lives -- 1.7 The Cybernetic Society -- 1.8 Wise Kings and Benevolent Dictators, Fueled by Big Data -- 1.9 Do We Need to Sacrifice Our Personal Freedom? -- 1.10 Who Will Rule the World? -- 1.11 Two Scenarios: Coercion or Freedom -- 1.12 A Better Future Ahead of Us -- 1.13 On the Way to a Smarter Digital Society -- References -- 2 Complexity Time Bomb -- 2.1 Phantom Traffic Jams -- 2.2 Recessions-Traffic Jams in the World Economy? -- 2.3 Systemic Instability -- 2.4 Beware of Strongly Coupled Systems! -- 2.5 Cascading Effects in Complex Networks -- 2.6 Large-Scale Power Blackouts -- 2.7 From Bankruptcy Cascades to Financial Crisis -- 2.8 A World Economic Crisis Results -- 2.9 Fundamental ("Radical") Uncertainty -- 2.10 Explosive Epidemics -- 2.11 Systemic Interdependence -- 2.12 Have Humans Created a "Complexity Time Bomb"? -- 2.13 Unintended Wars and Revolutions -- 2.14 Revolutionary Systemic Shifts -- 2.15 Conclusion -- 2.16 Appendix 1: How Harmless Behavior Can Become Critical -- 2.17 Appendix 2: Loss of Synchronization in Hierarchical Systems -- References -- 3 Social Forces -- 3.1 Measuring the World 2.0 -- 3.2 Monitoring the Flu and Other Diseases -- 3.3 Flu Prediction Better Than Google -- 3.4 Creating a Planetary Nervous System as a Citizen Web -- 3.5 Sociophysics: Revealing the Hidden Forces Governing Our Society -- 3.6 Social Forces Between Pedestrians -- 3.7 Self-Organization of Unidirectional Lanes in Pedestrian Counter-Flows.

What are the principles that keep our society together? By examining simple models of social interaction, this volume addresses this question, offering surprising insights into the social, "macro-level" outcomes and dynamics implied by individual, "micro-level" interactions.

This edition of Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioral changes based on social interaction processes. Originally, the crucial methods for the modeling of complex systems (stochastic methods and nonlinear dynamics) were developed in physics but they have very often proved their explanatory power in chemistry, biology, economics and the social sciences.Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces the most important concepts from nonlinear dynamics (synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches a very fundamental dynamic model is obtained which seems to open new perspectives in the social sciences. It includes many established models as special cases, e.g. the logistic equation, the gravity model, some diffusion models, the evolutionary game theory and the social field theory, but it also implies numerous new results. Examples concerning opinion formation, migration, social field theory, the self-organization of behavioral conventions as well as the behavior of customers and voters are presented and illustrated by computer simulations. This new edition adds chapters on Dynamic Decision Behavior, Optimal Self-Organization, Self-Organization in Space and Induced by Fluctuations, Drift- or Fluctuation-Induced Ordering and Self-Organization in Driven Many Particle Systems, Pattern Formation, Social Forces and Diffusion Instability in Games with Success-Driven Motion. Quantitative Sociodynamics is relevant both for social scientists and natural scientists who are interested in the application of stochastic and synergetics concepts to interdisciplinary topics.

I. Selbstorganisationsphänomene in Fußigängermengen -- 1. Einleitung -- 2. Empirische Fakten -- 3. Bisherige Modellierungsansätze -- 4. Das soziale Kräftemodell -- 5. Selbstorganisation kollektiver Phänomene -- 6. Optimierung von Fußgängeranlagen -- 7. Entstehung und Planung von Wegesystemen -- 8. Zusammenfassung -- II. Mikrosimulationsmodelle des Autobahnverkehrs und Verkehrsdaten -- 9. Einleitung -- 10. Verkehr in Zahlen -- 11. Empirische Fakten -- 12. Bisherige Modellierungsansätze -- 13. Ein Kräftemodell der Fahrzeugdynamik -- 14. Zusammenfassung und Ausblick -- III. Makroskopische Verkehrsflußmodelle und ihre mikroskopische Begründung -- 15. Einleitung -- 16. Nutzen makroskopischer Verkehrsmodelle -- 17. Geschichte makroskopischer Verkehrsmodelle -- 18. Mikroskopische Begründung gaskinetischer Gleichungen -- 19. Gaskinetische Herleitung makroskopischer Gleichungen -- 20. Dynamik bei hohen Dichten -- 21. Zusammenfassung -- Sach-, Namens- und Symbolverzeichnis.