Abstract
We propose a new task of automatically detecting reputation defence strategies in the field of computational argumentation. We cast the problem as relation classification, where given a pair of reputation threat and reputation defence, we determine the reputation defence strategy. We annotate a dataset of parliamentary questions and answers with reputation defence strategies. We then propose a model based on supervised learning to address the detection of these strategies, and report promising experimental results.
Cite
CITATION STYLE
Naderi, N., & Hirst, G. (2017). Recognizing reputation defence strategies in critical political exchanges. In International Conference Recent Advances in Natural Language Processing, RANLP (Vol. 2017-September, pp. 527–535). Incoma Ltd. https://doi.org/10.26615/978-954-452-049-6_069
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