@InProceedings{moreno-EtAl:2019:S19-2,
  author    = {Moreno, Jose G.  and  Pitarch, Yoann  and  Pinel-Sauvagnat, Karen  and  Hubert, Gilles},
  title     = {Rouletabille at SemEval-2019 Task 4: Neural Network Baseline for Identification of Hyperpartisan Publishers},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {981--984},
  abstract  = {This paper describes the Rouletabille participation to the Hyperpartisan News Detection task. We propose the use of different text classification methods for this task. Preliminary experiments using a similar collection used in (Potthast et al., 2018) show that neural-based classification methods reach state-of-the art results. Our final submission is composed of a unique run that ranks among all runs at 3/49 position for the by-publisher test dataset and 43/96 for the by-article test dataset in terms of Accuracy.},
  url       = {http://www.aclweb.org/anthology/S19-2169}
}