Dz-Emotion: Algerian Dialect Dataset for Emotion Detection

📌 Dataset Description

Dz-Emotion is the first large-scale, manually annotated dataset for emotion detection in Algerian Arabic dialect (Darija). The dataset consists of 6,000 social media comments, collected from YouTube, Facebook, and Instagram, and labeled according to Ekman’s six basic emotions:(Anger, Sadness, Fear, Disgust, Happiness, Surprise)

The dataset is designed to support research in Natural Language Processing (NLP) for low-resource dialects, especially Algerian Arabic.

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📄 Paper

For more information, please visit our paper:

👉 https://ieeexplore.ieee.org/document/11472633

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🤖 Related Model

This dataset was used to train:

• Dz-EmoBERT
  https://huggingface.co/Houdna-khilouf/Dz-EmoBERT

Dz-EmoBERT is a fine-tuned transformer model for emotion detection in Algerian dialect text, achieving 94.08% accuracy on this dataset.

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📊 Dataset Structure

The dataset is provided as a CSV file with the following columns:

Column	Description
ID	Unique identifier for each comment
Text	The comment text (Algerian dialect)
Label	Emotion label
Source	Platform source (YouTube, Facebook, Instagram)

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📈 Dataset Statistics

• Total samples: 6,000
• Classes: 6 emotions
• Samples per class: 1,000 (balanced)

Emotion Distribution:

• Anger: 1000
• Sadness: 1000
• Fear: 1000
• Disgust: 1000
• Happiness: 1000
• Surprise: 1000

Data Sources:

• YouTube: 53%
• Instagram: 29%
• Facebook: 18%

Train/Test Split:

• Train: 80% (4,800 samples)
• Validation: 20% (1,200 samples)

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🚀 Baseline Results

The dataset was used to fine-tune several models:

Model	Accuracy
ARBERT	86.00%
MARBERT	91.67%
Dz-EmoBERT	94.08%

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⚠️ Limitations

• Data collected from social media may include noise and bias
• Focused only on six emotions (Ekman model)
• Limited to Algerian dialect

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📩 Contact

For any questions or collaboration opportunities:

h.khilouf@univ-eltarf.dz

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📚 Citation

If you use this dataset, please cite:

@inproceedings{khilouf2025dzemotion,
  title={Dz-Emotion: An Algerian Dialect Dataset for Text-Based Emotion Detection},
  author={Khilouf, Houdna and Ziani, Amel and Malek, Nada Ahmed and Schwab, Didier and Yakoubi, Mohamed Amine},
  booktitle={2025 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI)},
  pages={1--6},
  year={2025},
  address={Sousse, Tunisia},
  doi={10.1109/ICRAMI64946.2025.11472633}
}