Complex contagion process in spreading of online innovation

Márton Karsai*, Gerardo Iñiguez, Kimmo Kaski, János Kertész

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract (may include machine translation)

Diffusion of innovation can be interpreted as a social spreading phenomenon 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, as 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 socio-economic development of a country.

Original languageEnglish
Article number20140694
JournalJournal of the Royal Society Interface
Volume11
Issue number101
DOIs
StatePublished - 6 Dec 2014

Keywords

  • Complex contagion phenomena
  • Data-driven modelling
  • Mean-field approximation

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