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SENSITIVITY TO NOISE VARIANCE IN A SOCIAL NETWORK DYNAMICS MODELPowerPoint Presentation

SENSITIVITY TO NOISE VARIANCE IN A SOCIAL NETWORK DYNAMICS MODEL

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### SENSITIVITY TO NOISE VARIANCE IN A SOCIAL NETWORK DYNAMICS MODEL

Hoan K. Nguyen

Center for Research in Scientific Computation

North Carolina State University

LVSS Transition Workshop

SAMSI

November 10-11, 2005

Collaborators: H.T Banks, A.F. Karr, and J.R. Samuels, Jr.

TALK OVERVIEW

- Mathematical Model
- An Example
- Numerical Results
- Conclusions and Future work

FANTASY OR REALITY?

Noise Dominated

??

??

Noise Enriched

Noise Enlarged

??

Essentially Deterministic

AN EXAMPLE

- 10 agents (A1, A2,…,AN)
- Each agent has 2 observable characteristics
- Sociability quotient ( ) : -10 (loners) 10 (people lovers)
- Outlook on life ( ) : -10 (negative outlook) 10 (positive outlook)

- determine different clustering scenarios
- : 1 cluster; : 2 clusters;
: 3 clusters

- : 1 cluster; : 2 clusters;

REGIME DEFINITION

- Fix to have single cluster scenario
- Essentially Deterministic:
- Both fate and path are as in the deterministic case

- Noise Enriched:
- Fate is the same as the deterministic case, but the set of paths is bigger

- Noise Enlarged:
- If fate is either a two cluster or a three cluster scenario described above

- Noise Dominated:
- No structured behavior at all

- is more sensitive to the regime than
- Noise Enlarged regime does not exist
- Model richness and flexibility (e.g., )
- Sensitivity Analysis
- Model Generalizations
- Links that are born and die
- Overlaid network (multi-dimensional links)

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