• Developed originally to model the dynamics of power grids and communication networks.
• This model allows us to naturally capture the different ways various factors (especially other people) can influence or alter the internal state of an individual.
• Computationally tractable
• All topologies are supported by this model

The parts of the model:

• Each node represents an individual as a full-fledged Markov Process.
• Each arrow represents some form of influence that one individual has on another.

C. Asavathiratham, "The Influence Model: A Tractable Representation for the Dynamics of Networked Markov Chains," in Dept. of EECS. Cambridge: MIT, 2000, pp. 188.