@inproceedings{hautli-janisz-etal-2022-disagreement,
    title = "Disagreement Space in Argument Analysis",
    author = "Hautli-Janisz, Annette  and
      Schad, Ella  and
      Reed, Chris",
    editor = "Abercrombie, Gavin  and
      Basile, Valerio  and
      Tonelli, Sara  and
      Rieser, Verena  and
      Uma, Alexandra",
    booktitle = "Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.nlperspectives-1.1",
    pages = "1--9",
    abstract = "For a highly subjective task such as recognising speaker intention and argumentation, the traditional way of generating gold standards is to aggregate a number of labels into a single one. However, this seriously neglects the underlying richness that characterises discourse and argumentation and is also, in some cases, straightforwardly impossible. In this paper, we present QT30nonaggr, the first corpus of non-aggregated argument annotation, which will be openly available upon publication. QT30nonaggr encompasses 10{\%} of QT30, the largest corpus of dialogical argumentation and analysed broadcast political debate currently available with 30 episodes of BBC{'}s {`}Question Time{'} from 2020 and 2021. Based on a systematic and detailed investigation of annotation judgements across all steps of the annotation process, we structure the disagreement space with a taxonomy of the types of label disagreements in argument annotation, identifying the categories of annotation errors, fuzziness and ambiguity.",
}