Abstract
How does network structure affect diffusion? Recent studies suggest that the
answer depends on the type of contagion. Complex contagions, unlike infectious
diseases (simple contagions), are affected by social reinforcement and
homophily. Hence, the spread within highly clustered communities is enhanced,
while diffusion across communities is hampered. A common hypothesis is that
memes and behaviors are complex contagions. We show that, while most memes
indeed behave like complex contagions, a few viral memes spread across many
communities, like diseases. We demonstrate that the future popularity of a meme
can be predicted by quantifying its early spreading pattern in terms of
community concentration. The more communities a meme permeates, the more viral
it is. We present a practical method to translate data about community
structure into predictive knowledge about what information will spread widely.
This connection may lead to significant advances in computational social
science, social media analytics, and marketing applications.
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