We propose a novel factor graph model for argument mining, designed for
settings in which the argumentative relations in a document do not necessarily
form a tree structure. (This is the case in over 20% of the web comments
dataset we release.)..
Our model jointly learns elementary unit type
classification and argumentative relation prediction. Moreover, our model
supports SVM and RNN parametrizations, can enforce structure constraints (e.g.,
transitivity), and can express dependencies between adjacent relations and
propositions. Our approaches outperform unstructured baselines in both web
comments and argumentative essay datasets.