  Mobile P2P technology provides a scalable approach to content delivery to a
large number of users on their mobile devices. In this work, we study the
dissemination of a \emph{single} content (e.g., an item of news, a song or a
video clip) among a population of mobile nodes. Each node in the population is
either a \emph{destination} (interested in the content) or a potential
\emph{relay} (not yet interested in the content). There is an interest
evolution process by which nodes not yet interested in the content (i.e.,
relays) can become interested (i.e., become destinations) on learning about the
popularity of the content (i.e., the number of already interested nodes). In
our work, the interest in the content evolves under the \emph{linear threshold
model}. The content is copied between nodes when they make random contact. For
this we employ a controlled epidemic spread model. We model the joint evolution
of the copying process and the interest evolution process, and derive the joint
fluid limit ordinary differential equations. We then study the selection of the
parameters under the content provider's control, for the optimization of
various objective functions that aim at maximizing content popularity and
efficient content delivery.
