So, the topics of leaders on tree t are directly sampled from the topic mixture θ t .
to model the internal topic correlations within the subgraph of conversation tree consisting of a leader and all its followers, we capture parentchild topic transitions π k ∼ Dir(γ), which is a distribution over K topics, and use π k,j to denote the probability of a follower assigned topic j when the topic of its parent is k. if message m is sampled as a follower and the topic assignment to its parent message is z t,p(m) , where p(m) indexes the parent of m, then z t,m (i.e., the topic of m) is generated from topic transition distribution π z t,p(m) .