Model Description
- Developed by: Cristina España-Bonet
- Model type: Binary stance classifier on top of XLM-RoBERTa
- Language(s) (NLP): English, German and Spanish
- License: LGPL
- Finetuned from model: XLM-RoBERTa Large
Model Sources
- Repository: https://github.com/cristinae/docTransformer
- Data: https://zenodo.org/records/8417761
- Paper: https://aclanthology.org/2023.findings-emnlp.787/
Direct Use
Determine the political stance of a (newspaper) article. Binary classification: left vs. right stance
Evaluation
srun --ntasks 1 --gpus-per-task 1 python -u docClassifier.py --task evaluation -f ./ -o politicalStanceLvsR_en.bin --test_dataset your.test
Classification
srun --ntasks 1 --gpus-per-task 1 python -u docClassifier.py --task classification -f ./ -o politicalStanceLvsR_en.bin --test_dataset your.test
Citation [optional]
BibTeX:
@inproceedings{espana-bonet:2023,
title = "Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a {C}hat{GPT} and Bard Newspaper",
author = "Espa{\~n}a-Bonet, Cristina",
editor = "Bouamor, Houda and Pino, Juan and Bali, Kalika",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2023",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-emnlp.787",
doi = "10.18653/v1/2023.findings-emnlp.787",
pages = "11757--11777"
}
APA:
España-Bonet, Cristina. (2023, December). Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a ChatGPT and Bard Newspaper. In Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 11757-11777).