  Rumor models consider that information transmission occurs with the same
probability between each pair of nodes. However, this assumption is not
observed in social networks, which contain influential spreaders. To overcome
this limitation, we assume that central individuals have a higher capacity of
convincing their neighbors than peripheral subjects. By extensive numerical
simulations we find that the spreading is improved in scale-free networks when
the transmission probability is proportional to PageRank, degree, and
betweenness centrality. In addition, the results suggest that the spreading can
be controlled by adjusting the transmission probabilities of the most central
nodes. Our results provide a conceptual framework for understanding the
interplay between rumor propagation and heterogeneous transmission in social
networks.
