@InProceedings{zehe-EtAl:2019:S19-2,
  author    = {Zehe, Albin  and  Hettinger, Lena  and  Ernst, Stefan  and  Hauptmann, Christian  and  Hotho, Andreas},
  title     = {Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1047--1051},
  abstract  = {This paper describes our system for the SemEval 2019 Task 4 on hyperpartisan news detection. We build on an existing deep learning approach for sentence classification based on a Convolutional Neural Network. Modifying the original model with additional layers to increase its expressiveness and finally building an ensemble of multiple versions of the model, we obtain an accuracy of 67.52\% and an F1 score of 73.78\% on the main test dataset. We also report on additional experiments incorporating handcrafted features into the CNN and using it as a feature extractor for a linear SVM.},
  url       = {http://www.aclweb.org/anthology/S19-2183}
}