In this talk, I will present recent work done in the CLaC laboratory on the use of discourse relations for blog summarization. Specifically, we measured the usefulness of 6 discourse relations - namely comparison, contingency, illustration, attribution, topic-opinion, and attributive for the task of text summarization from blogs. We have evaluated the effect of each relation using the Text Analysis Conference (TAC) 2008 opinion summarization dataset and compared them to the dataset of the Document Understanding Conference (DUC) 2007. The results show that for both textual genres, discourse relations seem to be as useful; contingency, comparison, and illustration relations have the greatest impact on the result of summarization; while attribution, topic-opinion, and attributive relations have the least effect in both types of texts. These results indicate that, at least for summarization, discourse relations are just as useful for informal and affective texts - those found in the social media - as for more traditional news articles.