@InProceedings{piotrkowicz-dimitrova-markert:2017:EACLSRW17,
  author    = {Piotrkowicz, Alicja  and  Dimitrova, Vania  and  Markert, Katja},
  title     = {Automatic Extraction of News Values from Headline Text},
  booktitle = {Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {64--74},
  abstract  = {Headlines play a crucial role in attracting audiences' attention to online
	artefacts (e.g. news articles, videos, blogs). The ability to carry out an
	automatic, large-scale analysis of headlines is critical to facilitate the
	selection and prioritisation of a large volume of digital content. In
	journalism studies news content has been extensively studied using manually
	annotated news values - factors used implicitly and explicitly when making
	decisions on the selection and prioritisation of news items. This paper
	presents the first attempt at a fully automatic extraction of news values from
	headline text. The news values extraction methods are applied on a large
	headlines corpus collected from The Guardian, and evaluated by comparing it
	with a manually annotated gold standard. A crowdsourcing survey indicates that
	news values affect people's decisions to click on a headline, supporting the
	need
	for an automatic news values detection.},
  url       = {http://www.aclweb.org/anthology/E17-4007}
}