@InProceedings{alkhatib-EtAl:2016:COLING,
  author    = {Al Khatib, Khalid  and  Wachsmuth, Henning  and  Kiesel, Johannes  and  Hagen, Matthias  and  Stein, Benno},
  title     = {A News Editorial Corpus for Mining Argumentation Strategies},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {3433--3443},
  abstract  = {Many argumentative texts, and news editorials in particular, follow a specific
	strategy to persuade their readers of some opinion or attitude. This includes
	decisions such as when to tell an anecdote or where to support an assumption
	with statistics, which is reflected by the composition of different types of
	argumentative discourse units in a text. While several argument mining corpora
	have recently been published, they do not allow the study of argumentation
	strategies due to incomplete or coarse-grained unit annotations. This paper
	presents a novel corpus with 300 editorials from three diverse news portals
	that provides the basis for mining argumentation strategies. Each unit in all
	editorials has been assigned one of six types by three annotators with a high
	Fleiss’ Kappa agreement of 0.56. We investigate various challenges of the
	annotation process and we conduct a first corpus analysis. Our results reveal
	different strategies across the news portals, exemplifying the benefit of
	studying editorials—a so far underresourced text genre in argument mining.},
  url       = {http://aclweb.org/anthology/C16-1324}
}