MidhunKanadan/populist-argument-schemes

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