@InProceedings{hanawa-EtAl:2019:S19-2,
  author    = {Hanawa, Kazuaki  and  Sasaki, Shota  and  Ouchi, Hiroki  and  Suzuki, Jun  and  Inui, Kentaro},
  title     = {The Sally Smedley Hyperpartisan News Detector at SemEval-2019 Task 4},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1057--1061},
  abstract  = {This paper describes our system submitted to the formal run of SemEval-2019 Task 4: Hyperpartisan news detection. Our system is based on a linear classifier using several features, i.e., 1) embedding features based on the pre-trained BERT embeddings, 2) article length features, and 3) embedding features of informative phrases extracted from by-publisher dataset. Our system achieved 80.9\% accuracy on the test set for the formal run and got the 3rd place out of 42 teams.},
  url       = {http://www.aclweb.org/anthology/S19-2185}
}