  It is commonly believed that information spreads between individuals like a
pathogen, with each exposure by an informed friend potentially resulting in a
naive individual becoming infected. However, empirical studies of social media
suggest that individual response to repeated exposure to information is
significantly more complex than the prediction of the pathogen model. As a
proxy for intervention experiments, we compare user responses to multiple
exposures on two different social media sites, Twitter and Digg. We show that
the position of the exposing messages on the user-interface strongly affects
social contagion. Accounting for this visibility significantly simplifies the
dynamics of social contagion. The likelihood an individual will spread
information increases monotonically with exposure, while explicit feedback
about how many friends have previously spread it increases the likelihood of a
response. We apply our model to real-time forecasting of user behavior.
