  Discourse relations among arguments reveal logical structures of a debate
conversation. However, no prior work has explicitly studied how the sequence of
discourse relations influence a claim's impact. This paper empirically shows
that the discourse relations between two arguments along the context path are
essential factors for identifying the persuasive power of an argument. We
further propose DisCOC to inject and fuse the sentence-level structural
discourse information with contextualized features derived from large-scale
language models. Experimental results and extensive analysis show that the
attention and gate mechanisms that explicitly model contexts and texts can
indeed help the argument impact classification task defined by Durmus et al.
(2019), and discourse structures among the context path of the claim to be
classified can further boost the performance.
