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%.