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While reigning models of diffusion have privileged the structure of a givensocial network as the key to informational exchange, real human interactions donot appear to take place on a single graph of connections. Using data collectedfrom a pilot study of the spread of HIV awareness in social networks ofhomeless youth, we show that health information did not diffuse in the fieldaccording to the processes outlined by dominant models. Since physical networkdiffusion scenarios often diverge from their more well-studied counterparts ondigital networks, we propose an alternative Activation Jump Model (AJM) thatdescribes information diffusion on physical networks from a multi-agent teamperspective. Our model exhibits two main differentiating features from leadingcascade and threshold models of influence spread: 1) The structural compositionof 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 theAJM significantly outperforms existing models in its fit to the observednode-level influence data on the youth networks. We then prove theoreticalresults, showing that the AJM exhibits many well-behaved properties shared bydominant models. Our results suggest that the AJM presents a flexible and moreaccurate model of network diffusion that may better inform influencemaximization in the field.

Activating the "Breakfast Club": Modeling Influence Spread in Natural-World Social Networks