cristinae/roberta_politicalStanceClassifier

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).