Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection

Zhiyuan Ning; Yuanzhen Lin; Ruichao Zhong

doi:10.18653/v1/S19-2181

Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection

Zhiyuan Ning, Yuanzhen Lin, Ruichao Zhong

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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.

Anthology ID:: S19-2181
Volume:: Proceedings of the 13th International Workshop on Semantic Evaluation
Month:: June
Year:: 2019
Address:: Minneapolis, Minnesota, USA
Editors:: Jonathan May, Ekaterina Shutova, Aurelie Herbelot, Xiaodan Zhu, Marianna Apidianaki, Saif M. Mohammad
Venue:: SemEval
SIG:: SIGLEX
Publisher:: Association for Computational Linguistics
Note:
Pages:: 1037–1040
Language:
URL:: https://aclanthology.org/S19-2181/
DOI:: 10.18653/v1/S19-2181
Bibkey:
Cite (ACL):: Zhiyuan Ning, Yuanzhen Lin, and Ruichao Zhong. 2019. Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1037–1040, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):: Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection (Ning et al., SemEval 2019)
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PDF:: https://aclanthology.org/S19-2181.pdf

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@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://aclanthology.org/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."
}

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%0 Conference Proceedings
%T Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection
%A Ning, Zhiyuan
%A Lin, Yuanzhen
%A Zhong, Ruichao
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F ning-etal-2019-team
%X 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.
%R 10.18653/v1/S19-2181
%U https://aclanthology.org/S19-2181/
%U https://doi.org/10.18653/v1/S19-2181
%P 1037-1040

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Markdown (Informal)

[Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection](https://aclanthology.org/S19-2181/) (Ning et al., SemEval 2019)

Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection (Ning et al., SemEval 2019)

ACL

Zhiyuan Ning, Yuanzhen Lin, and Ruichao Zhong. 2019. Team Peter-Parker at SemEval-2019 Task 4: BERT-Based Method in Hyperpartisan News Detection. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1037–1040, Minneapolis, Minnesota, USA. Association for Computational Linguistics.