  As a social media, online social networks play a vital role in the social
information diffusion. However, due to its unique complexity, the mechanism of
the diffusion in online social networks is different from the ones in other
types of networks and remains unclear to us. Meanwhile, few works have been
done to reveal the coupled dynamics of both the structure and the diffusion of
online social networks. To this end, in this paper, we propose a model to
investigate how the structure is coupled with the diffusion in online social
networks from the view of weak ties. Through numerical experiments on
large-scale online social networks, we find that in contrast to some previous
research results, selecting weak ties preferentially to republish cannot make
the information diffuse quickly, while random selection can achieve this goal.
However, when we remove the weak ties gradually, the coverage of the
information will drop sharply even in the case of random selection. We also
give a reasonable explanation for this by extra analysis and experiments.
Finally, we conclude that weak ties play a subtle role in the information
diffusion in online social networks. On one hand, they act as bridges to
connect isolated local communities together and break through the local
trapping of the information. On the other hand, selecting them as preferential
paths to republish cannot help the information spread further in the network.
As a result, weak ties might be of use in the control of the virus spread and
the private information diffusion in real-world applications.

Social and Information Networks;Statistical Mechanics;Physics and Society