@InProceedings{naderi-hirst:2017:RANLP2,
  author    = {Naderi, Nona  and  Hirst, Graeme},
  title     = {Classifying Frames at the Sentence Level in News Articles},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {536--542},
  abstract  = {Previous approaches to generic frame classification analyze frames at the
	document level. Here, we propose a supervised based approach based on deep
	neural networks and distributional representations for classifying frames at
	the sentence level in news articles. We conduct our experiments on the publicly
	available Media Frames Corpus compiled from the U.S. Newspapers. Using (B)LSTMs
	and GRU networks to represent the meaning of frames, we demonstrate that our
	approach yields at least 14-point improvement over several baseline methods.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_070}
}