@inproceedings{knauth-2019-orwellian,
    title = "Orwellian-times at {S}em{E}val-2019 Task 4: A Stylistic and Content-based Classifier",
    author = {Knauth, J{\"u}rgen},
    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/iwcs-25-ingestion/S19-2168/",
    doi = "10.18653/v1/S19-2168",
    pages = "976--980",
    abstract = "While fake news detection received quite a bit of attention in recent years, hyperpartisan news detection is still an underresearched topic. This paper presents our work towards building a classification system for hyperpartisan news detection in the context of the SemEval2019 shared task 4. We experiment with two different approaches - a more stylistic one, and a more content related one - achieving average results."
}