I have a new revision available on arxiv of the paper What stops social epidemics? I’ll be presenting the paper at ICWSM 2011 in Barcelona.

How likely is it for a virus or piece of information to spread through a network? If, on average, each person spreads the virus to more than one person than the virus will propagate through the entire network, an epidemic. If, on the other hand, each person spreads it to less than one person, the outbreak will die out very quickly, most likely after a handful of people have seen it.

For social epidemics on the Digg network, neither of these things happened. Stories would spread to a few hundred friends in the network, then stop without reaching even 0.1% of the whole network. There are many reasons for the slow-down of epidemics, but we identified two crucial, complementary ingredients.

• Most people who are exposed to a story are exposed by multiple friends
• More friends exposing you to a story does not make you more likely to spread the story yourself

Why does this slow down the epidemic? The first (primary) story spreader exposes some number of new people. Some fraction of those people are interested and spread the story themselves. If the people following these new (secondary) spreaders were a new, totally random group of people that looked just like the one the first spreader had, the story would merrily keep spreading. This kind of assumption is, roughly, a “mean field approximation”. But that’s not what happens. Instead, many of the friends of the secondary spreaders were already exposed by the primary spreader. Those people didn’t spread the story after one exposure, and they will continue to ignore it now. Fewer new people are reached in each round of spreading until the story dies out with a whimper.