  In online discussion fora, speakers often make arguments for or against
something, say birth control, by highlighting certain aspects of the topic. In
social science, this is referred to as issue framing. In this paper, we
introduce a new issue frame annotated corpus of online discussions. We explore
to what extent models trained to detect issue frames in newswire and social
media can be transferred to the domain of discussion fora, using a combination
of multi-task and adversarial training, assuming only unlabeled training data
in the target domain.
