@inproceedings{naderi-hirst-2017-recognizing,
    title = "Recognizing Reputation Defence Strategies in Critical Political Exchanges",
    author = "Naderi, Nona  and
      Hirst, Graeme",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
    month = sep,
    year = "2017",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/fix-sig-urls/R17-1069/",
    doi = "10.26615/978-954-452-049-6_069",
    pages = "527--535",
    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."
}