  Diffusion of innovation can be interpreted as a social spreading phenomena
governed by the impact of media and social interactions. Although these
mechanisms have been identified by quantitative theories, their role and
relative importance are not entirely understood, since empirical verification
has so far been hindered by the lack of appropriate data. Here we analyse a
dataset recording the spreading dynamics of the world's largest Voice over
Internet Protocol service to empirically support the assumptions behind models
of social contagion. We show that the rate of spontaneous service adoption is
constant, the probability of adoption via social influence is linearly
proportional to the fraction of adopting neighbours, and the rate of service
termination is time-invariant and independent of the behaviour of peers. By
implementing the detected diffusion mechanisms into a dynamical agent-based
model, we are able to emulate the adoption dynamics of the service in several
countries worldwide. This approach enables us to make medium-term predictions
of service adoption and disclose dependencies between the dynamics of
innovation spreading and the socioeconomic development of a country.
