Quantitative Sociodynamics [electronic resource] : Stochastic Methods and Models of Social Interaction Processes /
Helbing, Dirk.author.
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. .
Description based upon print version of record.
Includes bibliographical references and index.
and Summary -- Dynamic Decision Behavior -- 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 -- Quantitative Models of Social Processes -- Problems and Terminology -- Decision Theoretical Specification of the Transition Rates -- Opinion Formation Models -- Social Fields and Social Forces -- Evolutionary Game Theory Game theory!evolutionary|bb  -- Determination of the Model Parameters from Empirical Data Empirical experience|bb .
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. .
Probabilities.
Operations research.
Decision making.
Game theory.
Sociophysics.
Econophysics.
Social sciences.
Probability Theory and Stochastic Processes.
Operations Research/Decision Theory.
Game Theory, Economics, Social and Behav. Sciences.
Data-driven Science, Modeling and Theory Building.
Social Sciences, general.