Rouletabille at SemEval-2019 Task 4: Neural Network Baseline for Identification of Hyperpartisan Publishers

Jose G. Moreno, Yoann Pitarch, Karen Pinel-Sauvagnat, Gilles Hubert


Abstract
This paper describes the Rouletabille participation to the Hyperpartisan News Detection task. We propose the use of different text classification methods for this task. Preliminary experiments using a similar collection used in (Potthast et al., 2018) show that neural-based classification methods reach state-of-the art results. Our final submission is composed of a unique run that ranks among all runs at 3/49 position for the by-publisher test dataset and 43/96 for the by-article test dataset in terms of Accuracy.
Anthology ID:
S19-2169
Volume:
Proceedings of the 13th International Workshop on Semantic Evaluation
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota, USA
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
981–984
Language:
URL:
https://aclanthology.org/S19-2169
DOI:
10.18653/v1/S19-2169
Bibkey:
Cite (ACL):
Jose G. Moreno, Yoann Pitarch, Karen Pinel-Sauvagnat, and Gilles Hubert. 2019. Rouletabille at SemEval-2019 Task 4: Neural Network Baseline for Identification of Hyperpartisan Publishers. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 981–984, Minneapolis, Minnesota, USA. Association for Computational Linguistics.
Cite (Informal):
Rouletabille at SemEval-2019 Task 4: Neural Network Baseline for Identification of Hyperpartisan Publishers (Moreno et al., SemEval 2019)
Copy Citation:
PDF:
https://aclanthology.org/S19-2169.pdf