In this paper, we propose a simple and effective method for learning affective events that only requires a very small seed lexicon and a large raw corpus. As illustrated in Figure FIGREF1, our key idea is that we can exploit discourse relations BIBREF4 to efficiently propagate polarity from seed predicates that directly report one's emotions (e.g., “to be glad” is positive). 
 Question: How does their model learn using mostly raw data?
by exploiting discourse relations to propagate polarity from seed predicates to final sentiment polarity