  While reigning models of diffusion have privileged the structure of a given
social network as the key to informational exchange, real human interactions do
not appear to take place on a single graph of connections. Using data collected
from a pilot study of the spread of HIV awareness in social networks of
homeless youth, we show that health information did not diffuse in the field
according to the processes outlined by dominant models. Since physical network
diffusion scenarios often diverge from their more well-studied counterparts on
digital networks, we propose an alternative Activation Jump Model (AJM) that
describes information diffusion on physical networks from a multi-agent team
perspective. Our model exhibits two main differentiating features from leading
cascade and threshold models of influence spread: 1) The structural composition
of a seed set team impacts each individual node's influencing behavior, and 2)
an influencing node may spread information to non-neighbors. We show that the
AJM significantly outperforms existing models in its fit to the observed
node-level influence data on the youth networks. We then prove theoretical
results, showing that the AJM exhibits many well-behaved properties shared by
dominant models. Our results suggest that the AJM presents a flexible and more
accurate model of network diffusion that may better inform influence
maximization in the field.
