Control and Spread of Contagion in Networks

We study proliferation of an action in a network coordination game that is generalized to include tractable, model-based measure virality make it more realistic. present new algorithms compute contagion thresholds and equilibrium depth prove their theoretical properties. These apply arbitrary connected networks starting sets, both with without virality. Our are easy implement help quantify relationships previously inaccessible due computational intractability. Using these algorithms, we the spread scale-free 1,000 players using millions Monte Carlo simulations. results highlight channels through which may networks. Small sets lead greater less Virality amplifies effect larger set full inevitable cases where would not occur otherwise. It also brings dynamics closer type singularity. model analysis can be used understand potential consequences policies designed control or