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Quantitative Sociodynamics

Stochastic Methods and Models of Social Interaction Processes

  • Book
  • © 2010

Overview

Authors:
  1. Dirk Helbing

    1. Chair of Sociology, in particular of Mod, CLU E 1, ETH Zurich, Swiss Federal Institute of T, Zurich, Switzerland

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  • Unified and comprehensive overview of stochastic methods to describe quantitatively behavioral changes based on social interaction processes.
  • Presents numerous applications of the theoretical concepts.
  • New 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.

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xxix
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  2. Stochastic Methods and Non-linear Dynamics

    1. Front Matter

      Pages 47-48
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    1. Introduction and Summary

      • Dirk Helbing
      Pages 1-15

    2. Dynamic Decision Behavior

      • Dirk Helbing
      Pages 17-45

  4. Stochastic Methods and Non-linear Dynamics

    1. Front Matter

      Pages 47-48
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    2. Master Equation in State Space

      • Dirk Helbing
      Pages 49-81

    3. Boltzmann-Like Equations

      • Dirk Helbing
      Pages 83-98

    4. Master Equation in Configuration Space

      • Dirk Helbing
      Pages 99-113

    5. The Fokker-Planck Equation

      • Dirk Helbing
      Pages 115-133

    6. Langevin Equations and Non-linear Dynamics

      • Dirk Helbing
      Pages 135-149

  5. Quantitative Models of Social Processes

    1. Front Matter

      Pages 151-152
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    2. Problems and Terminology

      • Dirk Helbing
      Pages 153-165

    3. Decision Theoretical Specification of the Transition Rates

      • Dirk Helbing
      Pages 167-186

    4. Opinion Formation Models

      • Dirk Helbing
      Pages 187-223

    5. Social Fields and Social Forces

      • Dirk Helbing
      Pages 225-245

    6. Evolutionary Game Theory

      • Dirk Helbing
      Pages 247-274

    7. Determination of the Model Parameters from Empirical Data

      • Dirk Helbing
      Pages 275-309

  6. Back Matter

    Pages 311-333
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Keywords

About this book

When I wrote the book Quantitative Sociodynamics, it was an early attempt to make methods from statistical physics and complex systems theory fruitful for the modeling and understanding of social phenomena. Unfortunately, the ?rst edition appeared at a quite prohibitive price. This was one reason to make these chapters available again by a new edition. The other reason is that, in the meantime, many of the methods discussed in this book are more and more used in a variety of different ?elds. Among the ideas worked out in this book are: 1 • a statistical theory of binary social interactions, • a mathematical formulation of social ?eld theory, which is the basis of social 2 force models, • a microscopic foundation of evolutionary game theory, based on what is known today as ‘proportional imitation rule’, a stochastic treatment of interactions in evolutionary game theory, and a model for the self-organization of behavioral 3 conventions in a coordination game. It, therefore, appeared reasonable to make this book available again, but at a more affordable price. To keep its original character, the translation of this book, which 1 D. Helbing, Interrelations between stochastic equations for systems with pair interactions. Ph- icaA 181, 29–52 (1992); D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of behavioral models. PhysicaA 196, 546–573 (1993). 2 D. Helbing, Boltzmann-like and Boltzmann-Fokker-Planck equations as a foundation of beh- ioral models. PhysicaA 196, 546–573 (1993); D.

Reviews

From the reviews:

“This ambitious volume aims to provide a comprehensive account of mathematical methods for the quantitative study of social processes, with a focus on stochastic methods. … To summarise, as an introduction to such mathematics, it is admirably comprehensive and goes through the various derivations in a careful step-by-step manner. … an excellent reference for those with some mathematical expertise in the area to refer to. For those who straddle the simulation and mathematical communities it could be very useful.” (Bruce Edmonds and Mario Paolucci, Journal of Artificial Societies and Social Simulation, April, 2012)

Authors and Affiliations

  • Chair of Sociology, in particular of Mod, CLU E 1, ETH Zurich, Swiss Federal Institute of T, Zurich, Switzerland

    Dirk Helbing

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