@InProceedings{daxenberger-EtAl:2017:EMNLP2017,
  author    = {Daxenberger, Johannes  and  Eger, Steffen  and  Habernal, Ivan  and  Stab, Christian  and  Gurevych, Iryna},
  title     = {What is the Essence of a Claim? Cross-Domain Claim Identification},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2055--2066},
  abstract  = {Argument mining has become a popular research area in NLP. It typically
	includes the identification of argumentative components, e.g. claims, as the
	central component of an argument. We perform a qualitative analysis across six
	different datasets and show that these appear to conceptualize claims quite
	differently. To learn about the consequences of such different
	conceptualizations of claim for practical applications, we carried out
	extensive experiments using state-of-the-art feature-rich and deep learning
	systems, to identify claims in a cross-domain fashion. While the divergent
	conceptualization of claims in different datasets is indeed harmful to
	cross-domain classification, we show that there are shared properties on the
	lexical level as well as system configurations that can help to overcome these
	gaps.},
  url       = {https://www.aclweb.org/anthology/D17-1218}
}