Quantitative Sociodynamics Stochastic Methods and Models of Social Interaction Processes /

This new 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 (stochast...

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Bibliographic Details
Main Author: Helbing, Dirk. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edition:2.
Subjects:
Online Access:https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-11546-2
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505 0 # |a Introduction and Summary -- Dynamic Decision Behavior -- Part I: Stochastic Methods and Non-Linear Dynamics: Master Equation in State Space -- Boltzmann-Like Equations -- Master Equation in Configuration Space -- The Fokker-Planck Equation -- Langevin Equations and Non-Linear Dynamics -- Part II: Quantitative Models of Social Processes: Overview -- Problems and Terminology -- Decision Theoretical Specification of the Transition Rates -- Opinion Formation Models -- Social Fields and Social Forces -- Evolutionary Game Theory -- Determination of the Model Parameters from Empirical Data -- List of Symbols used in Part I and II.-. 
520 # # |a This new 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 and mathematics, but they have very often proven their explanatory power in chemistry, biology, economics and the social sciences as well. Quantitative Sociodynamics provides a unified and comprehensive overview of the different stochastic methods, their interrelations and properties. In addition, it introduces important concepts from nonlinear dynamics (e.g. synergetics, chaos theory). The applicability of these fascinating concepts to social phenomena is carefully discussed. By incorporating decision-theoretical approaches, a fundamental dynamic model is obtained, which opens 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, evolutionary game theory�and social field theory. Moreover, it implies numerous new results and is relevant for various application areas, such as opinion formation, migration, the self-organization�of behavioral conventions, and the behavior of customers and voters.�Theoretical results are complemented and illustrated by numerous computer simulations. 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.� 
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