Summary

Framework

Ising model

• Given the Hamiltonian, wouldn't that mean that agents are biased towards being whatever is set to the negative state?
  • TODO: Read "Stat phys of soc dyn" section on this wayy more thoroughly
  • TODO: try with toy example

Network topology

• Agents sit on vertices of a network, and the edges define possible interaction patterns
• Types of synthetic network models
  • Random graph (ER model)
  • Small-world
  • Scale-freea
• Prototype homogenous network model is the random graph (ER model)
  • See notes on synthetic network structures

Dynamical systems

Notes

• Discusses several aspects of the basic question: "how do the interactions between social agents create order out of an initial disordered situation?"
  • Order meaning consensus, agreement, uniformity
• Key factor: agents interact and this tends to make people more similar; repeated interactions lead to higher degrees of homogeneity
• The modeling of social agents using simple models involves a large amount of simplification; the investigation of social dynamics models invovles two levels of difficulty:
  • Defining sensible and realistic microscopic models
  • Inferring macroscopic phenomenology out of the microscopic dynamics of such models
• While justifiably receiving criticism for too much simplification, statistical physics models of social systems

• Common theme of social dynamics is the transition from an initial disordered state to a configuration that displays order