  In this paper we propose a mechanistic model that links micro social
interactions to macro observables in the case of diffusion of film-going
decisions. We devise a generalized epidemic model to capture the temporal
evolution of box office revenues. The model adds social influence and memory
effects to conventional epidemic models. Fitting the model to a temporal data
set containing domestic weekly revenue of the 5000 top US-grossing films of all
time, we find that a two-parameter model can capture a remarkable portion of
the observed variance in the data. Using the distribution of the estimated
parameters for different genres, we then present a predictive model which
provides reasonable a-priori estimates of future sale as a function of time.
