Difference between revisions of "Diffusion models"
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* a threshold θ for each node selected uniformly at random | * a threshold θ for each node selected uniformly at random | ||
| − | At each step an inactive node becomes active if the sum of the weights of the edges with active neighbors exceeds threshold | + | At each step, an inactive node becomes active if the sum of the weights of the edges with active neighbors exceeds threshold |
[[File:Ltm.jpg]] | [[File:Ltm.jpg]] | ||
Revision as of 23:51, 30 March 2011
Diffusion models were originally used in social networks to model the spread of influence in a network. In these models each node is either active or inactive. Over iterations an inactive nodes becomes active as more of its neighbors become active.
Linear Threshold Model
The Linear Threshold Model is one of the most popular diffusion models.
Given
- a set of active nodes as seeds
- a threshold θ for each node selected uniformly at random
At each step, an inactive node becomes active if the sum of the weights of the edges with active neighbors exceeds threshold
