SUM 2013
Influence propagation in large graphs - theorems, algorithms, and case studies
by Christos Faloutsos, CMU
Description:
Given the specifics of a virus (or product, or hashtag)
how quickly will it propagate on a contact network?
Will it create an epidemic, or will it quickly die out?
The way a virus/product/meme propagates on a graph is important,
because it can help us design immunization policies
(if we want to stop it) or marketing policies
(if we want it to succeed).
We present some surprising results on the so-called 'epidemic threshold',
we discuss the effects of time-varying contact networks,
and we present fast algorithms to achieve near-optimal immunization.
Foils
Here