Quantitative Sociodynamics
Subtitle: Stochastic Methods and Models of Social Interaction Processes
By: by Dirk Helbing
Series: Theory and Decision Library, Series B: Mathematical and Statistical Methods -- 31; Theory and Decision Library, Series B: Mathematical and Statistical Methods -- 31
Publisher: Springer Netherlands
Published: 1995
Place of publication: Dordrecht
Language: eng
Format: [electronic resource] :
Number of pages: 339
ISBN-13: 9789048144822; 9789401585163
Subjects: Mathematics; Distribution (Probability theory); Physics; Operations research
Description: Quantitative Sociodynamics presents a general strategy for interdisciplinary model building and its application to a quantitative description of behavioural 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 behavioural conventions as well as the behaviour of customers and voters are presented and illustrated by 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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