license: mit
Populist Argument Schemes 🗣️
A curated dataset of translated tweets from four political leaders, annotated with argument schemes according to argumentation theory. The dataset enables fine-tuning and evaluation of language models for argument mining, rhetorical analysis, and populist discourse detection.
Dataset Summary
This dataset contains English-translated tweets from:
- Matteo Salvini 🇮🇹
- Jair Bolsonaro 🇧🇷
- Donald Trump 🇺🇸
- Joe Biden 🇺🇸
Each tweet is annotated with its primary argumentation scheme (based on Argument 1) following a scheme taxonomy inspired by Walton and Macagno. The dataset is derived from Fabrizio Macagno's original annotated corpus on the Language of Populism and translated for cross-lingual NLP applications.
Features
Politician: Name of the political figure (e.g., "Trump")Argument: The tweet text (translated into English)Argument Scheme: The full name of the primary argumentation scheme (e.g., "Argument from Consequences")
Argument Scheme Labels
The dataset includes 13 argument schemes:
| Code | Argument Scheme |
|---|---|
| AA | Argument from Analogy |
| AC | Argument from Consequences |
| AH | Ad Hominem |
| AS | Argument from Sign |
| AV | Argument from Values |
| BEX | Argument from Best Explanation |
| CE | Argument from Cause to Effect |
| CLASS | Argument from Classification |
| CO | Argument from Commitment |
| PK | Argument from Position to Know |
| PO | Argument from Popular Opinion |
| PR | Argument from Practical Reasoning |
| VV | Victimization |
Use Cases
This dataset can be used for:
- Fine-tuning LLMs for argument scheme classification
- Training models for argument mining and fallacy detection
- Studying populist rhetoric and comparative discourse analysis
- Building educational tools for teaching argumentation theory
How to Use 🧠
You can easily load this dataset using the 🤗 datasets library, which allows seamless integration with Hugging Face Transformers, evaluation tools, and fine-tuning pipelines.
📥 Load the Dataset
from datasets import load_dataset
# Load the dataset from the Hugging Face Hub
dataset = load_dataset("MidhunKanadan/populist-argument-schemes")
# View a sample entry
print(dataset["train"][0])
🖨️ Expected Output
{
'Politician': 'Biden',
'Argument': 'It matters whether you continue to wear a mask. It matters whether you continue to socially distance. It matters whether you wash your hands. It all matters and can help save lives.',
'Argument Scheme': 'ARGUMENT FROM CONSEQUENCES'
}
Citation
If you use this dataset, please cite the original author:
Macagno, F. (2022). Argumentation schemes, fallacies, and evidence in politicians' argumentative tweets – a coded dataset. Data in Brief, 44, 108501. https://doi.org/10.1016/j.dib.2022.108501