Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System

Rebekah Cramerus; Tatjana Scheffler

doi:10.18653/v1/S19-2178

Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System

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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.

Anthology ID:: S19-2178
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:: 1021–1025
Language:
URL:: https://aclanthology.org/S19-2178/
DOI:: 10.18653/v1/S19-2178
Bibkey:
Cite (ACL):: Rebekah Cramerus and Tatjana Scheffler. 2019. Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1021–1025, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):: Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System (Cramerus & Scheffler, SemEval 2019)
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PDF:: https://aclanthology.org/S19-2178.pdf

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@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://aclanthology.org/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."
}

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%0 Conference Proceedings
%T Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System
%A Cramerus, Rebekah
%A Scheffler, Tatjana
%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 cramerus-scheffler-2019-team
%X 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.
%R 10.18653/v1/S19-2178
%U https://aclanthology.org/S19-2178/
%U https://doi.org/10.18653/v1/S19-2178
%P 1021-1025

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Markdown (Informal)

[Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System](https://aclanthology.org/S19-2178/) (Cramerus & Scheffler, SemEval 2019)

Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System (Cramerus & Scheffler, SemEval 2019)

ACL

Rebekah Cramerus and Tatjana Scheffler. 2019. Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1021–1025, Minneapolis, Minnesota, USA. Association for Computational Linguistics.