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.

本文研究了信息传播的社会传染模型，并通过对两个不同的社交媒体网站 Twitter 和 Digg 的用户响应进行比较，证明了信息暴露的位置对社会传染的影响非常大。通过考虑信息在用户界面上的可见性，可以显著简化社会传染的动态模型，并且发现信息暴露次数和主动搜索信息的概率成正比。最后，本文将该模型应用于用户行为的实时预测。