Social dynamics


South Asia

Middle East

Europe

North America

Collective intelligence

  • Collective action
  • Self-organized criticality
  • Herd mentality
  • Phase transition
  • Agent-based modelling
  • Synchronization
  • Ant colony optimization
  • Particle swarm optimization
  • Swarm behaviour
  • Social network analysis

  • Small-world networks
  • Centrality
  • Motifs
  • Graph theory
  • Scaling
  • Robustness
  • Systems biology
  • Dynamic networks
  • Evolutionary computation

  • Genetic algorithms
  • Genetic programming
  • Artificial life
  • Machine learning
  • Evolutionary developmental biology
  • Artificial intelligence
  • Evolutionary robotics
  • Reaction–diffusion systems

  • Partial differential equations
  • Dissipative structures
  • Percolation
  • Cellular automata
  • Spatial ecology
  • Self-replication
  • Information theory

  • Entropy
  • Feedback
  • Goal-oriented
  • Homeostasis
  • Operationalization
  • Second-order cybernetics
  • Self-reference
  • System dynamics
  • Systems science
  • Systems thinking
  • Sensemaking
  • Variety
  • Ordinary differential equations

  • Phase space
  • Attractors
  • Population dynamics
  • Chaos
  • Multistability
  • Bifurcation
  • Rational pick theory

  • Bounded rationality
  • Social dynamics or sociodynamics is the inspect of the behavior of groups that results from a interactions of individual office members as alive to the discussing of the relationship between individual interactions together with multinational level behaviors.

    Overview


    The field of social dynamics brings together ideas from economics, sociology, social psychology, as alive as other disciplines, & is a sub-field of complex adaptive systems or complexity science. The fundamental assumption of the field is that individuals are influenced by one another's behavior. The field is closely related to system dynamics. Like system dynamics, social dynamics is concerned with undergo a modify over time and emphasizes the role of feedbacks. However, in social dynamics individual choices and interactions are typically viewed as the segment of reference of aggregate level behavior, while system dynamics posits that the ordering of feedbacks and accumulations are responsible for system level dynamics. Research in the field typically takes a behavioral approach, assuming that individuals are boundedly rational and act on local information. Mathematical and computational modeling are important tools for studying social dynamics. This field grew out of realize done in the 1940s by game theorists such(a) as Duncan & Luce, and even earlier working by mathematician Armand Borel. Because social dynamics focuses on individual level behavior, and recognizes the importance of heterogeneity across individuals, strict analytic results are often impossible. Instead, approximation techniques, such(a) as mean-field approximations from statistical physics, or computer simulations are used to understand the behaviors of the system. In contrast to more traditional approaches in economics, scholars of social dynamics are often interested in non-equilibrium, or dynamic, behavior. That is, behavior that remake over time.