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---
language:
- en
pretty_name: Enhanced Emotion Classification Dataset
version: 2.0
tags:
- text-classification
- emotion
- sentiment-analysis
- ekman-emotions
- text
license: mit
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# Enhanced Emotion Classification Dataset (v2.0)
## Dataset Description
This dataset is an enhanced version of the emotion classification dataset, including multiple sources of emotion data with Ekman emotion mapping. It contains a total of 240,426 samples across 7 emotion categories, with each sample labeled with its original data source.
### Dataset Structure
The dataset is split into three parts:
- **Train**: 186,619 samples (77.6%)
- **Validation**: 31,086 samples (12.9%)
- **Test**: 22,721 samples (9.4%)
### Emotion Categories
The dataset includes 7 Ekman basic emotions:
- neutral
- joy
- sadness
- anger
- fear
- surprise
- disgust
## Data Sources
The dataset combines data from 7 different sources:
1. **Movies_Reviews**
- Movie review emotion data
- Contains 7 emotion categories
2. **DailyDialog**
- Real dialog data with multi-turn conversations
- Contains 7 emotion categories
3. **GoEmotions**
- Reddit comment data with colloquial expressions
- Contains 7 emotion categories
4. **ISEAR**
- International emotion research data with high-quality text
- Contains 7 emotion categories
5. **MELD**
- Multimodal emotion dialog data from the TV show "Friends"
- Contains 7 emotion categories
6. **mteb_emotion**
- Emotion analysis dataset with various emotion expressions
- Contains 7 emotion categories
7. **Tweet Emotions**
- Twitter tweet data including @mentions
- Contains 7 emotion categories
## Data Format
Each CSV file contains the following columns:
- `text`: Text content
- `label_text`: Emotion label (one of the 7 emotion categories)
- `source`: Data source identifier (e.g., dailydialog, goemotions, tweetemotions, etc.)
## File Structure
```
dataset_huggingface_enhance/
├── train.csv # Merged training set (186,619 samples)
├── val.csv # Merged validation set (31,086 samples)
├── test.csv # Merged test set (22,721 samples)
├── README.md # Dataset documentation
├── dataset_infos.json # Hugging Face dataset configuration
├── info.md # Detailed dataset statistics
├── label_list.txt # List of emotion labels
└── stats.py # Dataset statistics script
```
## Usage
To use this dataset with Hugging Face Datasets library:
```python
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("jiangchengchengNLP/Enhanced_Emotion_Classification_Dataset")
# Access specific splits
train_dataset = dataset["train"]
val_dataset = dataset["validation"]
test_dataset = dataset["test"]
```
## Emotion Distribution
### Training Set (186,619 samples)
- neutral: 51.11%
- joy: 21.64%
- sadness: 7.98%
- anger: 5.97%
- fear: 5.90%
- surprise: 5.11%
- disgust: 2.29%
### Validation Set (31,086 samples)
- neutral: 40.96%
- joy: 24.15%
- sadness: 9.38%
- fear: 8.06%
- anger: 7.49%
- surprise: 7.06%
- disgust: 2.89%
### Test Set (22,721 samples)
- neutral: 45.11%
- joy: 22.88%
- sadness: 9.13%
- anger: 7.61%
- fear: 6.67%
- surprise: 5.93%
- disgust: 2.67%
## Notes
- The dataset has class imbalance, with neutral being the most common category (~40-51%) and disgust being the least common (~2-3%).
- Each sample includes a `source` field indicating its original data source, which allows for source-specific analysis.
- Different data sources have different text styles, which may affect model performance.
- The dataset uses Ekman emotion mapping, which maps various emotion labels to the 7 basic emotions.
## License
The dataset is released under the MIT License.
## Citation
If you use this dataset in your research, please cite the original datasets:
- DailyDialog: https://aclanthology.org/I17-1099/
- GoEmotions: https://arxiv.org/abs/2005.00547
- Tweet Emotions: https://www.aclweb.org/anthology/W18-6212/
- MELD: https://arxiv.org/abs/1810.02508
- ISEAR: https://link.springer.com/article/10.1007/BF02112196
## Version History
- **v2.0** (2026-01-07): Updated dataset with merged sources and source field
- Total samples: 240,426
- Added `source` field to all samples
- Updated emotion distribution statistics
- Improved data quality and consistency
- Filtered all NaN values from the dataset
- **v1.0**: Initial release
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