@inproceedings{zhang-etal-2019-ubc,
title = "{UBC}-{NLP} at {S}em{E}val-2019 Task 4: Hyperpartisan News Detection With Attention-Based {B}i-{LSTM}s",
author = "Zhang, Chiyu and
Rajendran, Arun and
Abdul-Mageed, Muhammad",
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/S19-2188",
doi = "10.18653/v1/S19-2188",
pages = "1072--1077",
abstract = "We present our deep learning models submitted to the SemEval-2019 Task 4 competition focused at Hyperpartisan News Detection. We acquire best results with a Bi-LSTM network equipped with a self-attention mechanism. Among 33 participating teams, our submitted system ranks top 7 (65.3{\%} accuracy) on the {`}labels-by-publisher{'} sub-task and top 24 out of 44 teams (68.3{\%} accuracy) on the {`}labels-by-article{'} sub-task (65.3{\%} accuracy). We also report a model that scores higher than the 8th ranking system (78.5{\%} accuracy) on the {`}labels-by-article{'} sub-task.",
}
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%0 Conference Proceedings
%T UBC-NLP at SemEval-2019 Task 4: Hyperpartisan News Detection With Attention-Based Bi-LSTMs
%A Zhang, Chiyu
%A Rajendran, Arun
%A Abdul-Mageed, Muhammad
%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 zhang-etal-2019-ubc
%X We present our deep learning models submitted to the SemEval-2019 Task 4 competition focused at Hyperpartisan News Detection. We acquire best results with a Bi-LSTM network equipped with a self-attention mechanism. Among 33 participating teams, our submitted system ranks top 7 (65.3% accuracy) on the ‘labels-by-publisher’ sub-task and top 24 out of 44 teams (68.3% accuracy) on the ‘labels-by-article’ sub-task (65.3% accuracy). We also report a model that scores higher than the 8th ranking system (78.5% accuracy) on the ‘labels-by-article’ sub-task.
%R 10.18653/v1/S19-2188
%U https://aclanthology.org/S19-2188
%U https://doi.org/10.18653/v1/S19-2188
%P 1072-1077
Markdown (Informal)
[UBC-NLP at SemEval-2019 Task 4: Hyperpartisan News Detection With Attention-Based Bi-LSTMs](https://aclanthology.org/S19-2188) (Zhang et al., SemEval 2019)
ACL