@inproceedings{cramerus-scheffler-2019-team,
    title = "Team Kit Kittredge at {S}em{E}val-2019 Task 4: {LSTM} Voting System",
    author = "Cramerus, Rebekah  and
      Scheffler, Tatjana",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/S19-2178/",
    doi = "10.18653/v1/S19-2178",
    pages = "1021--1025",
    abstract = "This paper describes the approach of team Kit Kittredge to SemEval-2019 Task 4: Hyperpartisan News Detection. The goal was binary classification of news articles into the categories of ``biased'' or ``unbiased''. We had two software submissions: one a simple bag-of-words model, and the second an LSTM (Long Short Term Memory) neural network, which was trained on a subset of the original dataset selected by a voting system of other LSTMs. This method did not prove much more successful than the baseline, however, due to the models' tendency to learn publisher-specific traits instead of general bias."
}