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While there is increasing interest in automatically recognizing the argumentative structure of a text, recognizing the argumentative purpose of revisions to such texts has been less explored. Furthermore, existing revision classification approaches typically ignore contextual information. We propose two approaches for utilizing contextual information when predicting argumentative revision purposes: developing contextual features for use in the classification paradigm of prior work, and transforming the classification problem to a sequence labeling task. Experimental results using two corpora of student essays demonstrate the utility of contextual information for predicting argumentative revision purposes.
Zhang et al. (Fri,) studied this question.