Abstract: With the development of the Social Networking Services (SNS),SNS has become an important tool for people to communicate with each other．The rich user generated contents (UCG) of SNS have contained useful knowledge about information propagation rules．Thus SNS can be used to study public opinion and information propagation rules in the social networks．As information propagation happens in the online social networks discretely and sparsely,it is hard to directly observe and study the propagation process of information in an online social network with over 10million nodes．To meet the challenges,the paper (1) provided a model “info-trajectory” to capture the information propagation pathways in the online social network,(2) proposed several algorithms to extract info-trajectory from some practical microblog social networks efficiently by employing repost timeline (a kind of public available repost notification data of microblog),(3) studied the temporal relations of the repost actions for the users on the obtained info-trajectories, (4) proposed algorithm K-advocators to discover the advocators from the information propagation trajectories and information propagation patterns in the microblog,and (5) in the experiment section,provided the sufficient experiments to study info-trajectories for several topics on Sinamicroblog(a prevalent microblog application in China),and several po-pular SNSs．The results show that the proposed methods are efficient to extract the info-trajectories,and useful to disco-ver advocators for specific topics in the microblogs.

Key words: Social network,Graph mining,Information trajectory