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
- 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:
- 981–984
- Language:
- URL:
- https://aclanthology.org/S19-2169
- DOI:
- 10.18653/v1/S19-2169
- 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)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/S19-2169.pdf