@InProceedings{bourgonje-morenoschneider-rehm:2017:NLPmJ,
  author    = {Bourgonje, Peter  and  Moreno Schneider, Julian  and  Rehm, Georg},
  title     = {From Clickbait to Fake News Detection: An Approach based on Detecting the Stance of Headlines to Articles},
  booktitle = {Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {84--89},
  abstract  = {We present a system for the detection of the stance of headlines with regard to
	their corresponding article bodies. The approach can be applied in fake news,
	especially clickbait detection scenarios. The component is part of a larger
	platform for the curation of digital content; we consider veracity and
	relevancy an increasingly important part of curating online information. We
	want to contribute to the debate on how to deal with fake news and related
	online phenomena with technological means, by providing means to separate
	related from unrelated headlines and further classifying the related headlines.
	On a publicly available data set annotated for the stance of headlines with
	regard to their corresponding article bodies, we achieve a (weighted) accuracy
	score of 89.59.},
  url       = {http://www.aclweb.org/anthology/W17-4215}
}