  Large cascades can develop in online social networks as people share
information with one another. Though simple reshare cascades have been studied
extensively, the full range of cascading behaviors on social media is much more
diverse. Here we study how diffusion protocols, or the social exchanges that
enable information transmission, affect cascade growth, analogous to the way
communication protocols define how information is transmitted from one point to
another. Studying 98 of the largest information cascades on Facebook, we find a
wide range of diffusion protocols - from cascading reshares of images, which
use a simple protocol of tapping a single button for propagation, to the ALS
Ice Bucket Challenge, whose diffusion protocol involved individuals creating
and posting a video, and then nominating specific others to do the same. We
find recurring classes of diffusion protocols, and identify two key
counterbalancing factors in the construction of these protocols, with
implications for a cascade's growth: the effort required to participate in the
cascade, and the social cost of staying on the sidelines. Protocols requiring
greater individual effort slow down a cascade's propagation, while those
imposing a greater social cost of not participating increase the cascade's
adoption likelihood. The predictability of transmission also varies with
protocol. But regardless of mechanism, the cascades in our analysis all have a
similar reproduction number ($\approx$ 1.8), meaning that lower rates of
exposure can be offset with higher per-exposure rates of adoption. Last, we
show how a cascade's structure can not only differentiate these protocols, but
also be modeled through branching processes. Together, these findings provide a
framework for understanding how a wide variety of information cascades can
achieve substantial adoption across a network.

Social and Information Networks;Physics and Society