@inproceedings{ning-etal-2019-team,
    title = "Team Peter-Parker at {S}em{E}val-2019 Task 4: {BERT}-Based Method in Hyperpartisan News Detection",
    author = "Ning, Zhiyuan  and
      Lin, Yuanzhen  and
      Zhong, Ruichao",
    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/S19-2181/",
    doi = "10.18653/v1/S19-2181",
    pages = "1037--1040",
    abstract = "This paper describes the team peter-parker{'}s participation in Hyperpartisan News Detection task (SemEval-2019 Task 4), which requires to classify whether a given news article is bias or not. We decided to use JAVA to do the article parsing tool and the BERT-Based model to do the bias prediction. Furthermore, we will show experiment results with analysis."
}