Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
English
ArXiv:
License:
| 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 | |