TY - JOUR
T1 - Complex contagion process in spreading of online innovation
AU - Karsai, Márton
AU - Iñiguez, Gerardo
AU - Kaski, Kimmo
AU - Kertész, János
N1 - Publisher Copyright:
© 2014 The Author(s) Published by the Royal Society. All rights reserved.
PY - 2014/12/6
Y1 - 2014/12/6
N2 - 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.
AB - 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.
KW - Complex contagion phenomena
KW - Data-driven modelling
KW - Mean-field approximation
UR - http://www.scopus.com/inward/record.url?scp=84928905761&partnerID=8YFLogxK
U2 - 10.1098/rsif.2014.0694
DO - 10.1098/rsif.2014.0694
M3 - Article
C2 - 25339685
AN - SCOPUS:84928905761
SN - 1742-5689
VL - 11
JO - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
IS - 101
M1 - 20140694
ER -