  Numerous studies have attempted to model the effect of mass media on the
transmission of diseases such as influenza, however quantitative data on media
engagement has until recently been difficult to obtain. With the recent
explosion of "big data" coming from online social media and the like, large
volumes of data on a population's engagement with mass media during an epidemic
are becoming available to researchers. In this study we combine an online data
set comprising millions of shared messages relating to influenza with
traditional surveillance data on flu activity to suggest a functional form for
the relationship between the two. Using this data we present a simple
deterministic model for influenza dynamics incorporating media effects, and
show that such a model helps explain the dynamics of historical influenza
outbreaks. Furthermore, through model selection we show that the proposed media
function fits historical data better than other media functions proposed in
earlier studies.
