  Follow-ship network among users underlies the diffusion dynamics of messages
on online social networks. Generally, the structure of underlying social
network determines the visibility of messages and the diffusion process. In
this paper, we study forwarding behavior of individuals, taking Sina Weibo as
an example. We investigate multiple exposures in information diffusion and the
"forwarding whom" problem associated with multiple exposures. Finally, we model
and predict the "forwarding whom" behavior of individuals, combining
structural, temporal, historical, and content features. Experimental results
demonstrate that our method achieves a high accuracy 91.3%.
