An Epidemiological Mechanistic Model of Box Office Dynamics

TL;DR

This paper introduces a mechanistic epidemic-inspired model that captures the dynamics of box office revenues by incorporating social influence and memory effects, effectively fitting historical data and predicting future sales.

Contribution

The paper develops a generalized epidemic model for film-going decisions that includes social influence and memory, fitting it to extensive box office data and enabling future revenue predictions.

Findings

A two-parameter model captures most variance in box office data.

Model fitting reveals genre-based parameter distributions.

Predictive estimates of future sales are reasonably accurate.

Abstract

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.