Duplicate from jiangchengchengNLP/Enhanced_Emotion_Classification_Dataset

Co-authored-by: BIGGOD <jiangchengchengNLP@users.noreply.huggingface.co>

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README.md

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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
+

dataset_infos.json

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+{
+  "default": {
+    "description": "Enhanced emotion classification dataset with multiple sources and Ekman emotion mapping",
+    "citation": "",
+    "homepage": "",
+    "license": "MIT",
+    "features": {
+      "text": {
+        "dtype": "string",
+        "id": null,
+        "_type": "Value"
+      },
+      "label_text": {
+        "dtype": "string",
+        "id": null,
+        "_type": "Value"
+      },
+      "source": {
+        "dtype": "string",
+        "id": null,
+        "_type": "Value"
+      }
+    },
+    "post_processed": null,
+    "supervised_keys": null,
+    "task_templates": [
+      {
+        "task": "text-classification",
+        "text_column": "text",
+        "label_column": "label_text"
+      }
+    ],
+    "builder_name": "csv",
+    "config_name": "default",
+    "version": {
+      "version_str": "2.0.0",
+      "description": "Updated dataset with merged sources and source field"
+    },
+    "splits": {
+      "train": {
+        "name": "train",
+        "num_bytes": 0,
+        "num_examples": 186639,
+        "dataset_name": "enhanced_emotion_classification"
+      },
+      "validation": {
+        "name": "validation",
+        "num_bytes": 0,
+        "num_examples": 31092,
+        "dataset_name": "enhanced_emotion_classification"
+      },
+      "test": {
+        "name": "test",
+        "num_bytes": 0,
+        "num_examples": 22722,
+        "dataset_name": "enhanced_emotion_classification"
+      }
+    }
+  }
+}

info.md

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+# 数据集统计信息
+
+## 概览
+
+- **总样本数**: 240,426 条
+- **训练集**: 186,619 (77.62%)
+- **验证集**: 31,086 (12.93%)
+- **测试集**: 22,721 (9.45%)
+- **情感类别**: 7种（neutral + 6种Ekman基本情感）
+- **数据源**: 7个（Movies_Reviews, dailydialog, goemotions, isear, meld, mteb_emotion, tweetemotions）
+
+## 数据集列表
+
+### 合并数据集（按子集）
+
+| 子集 | 样本数 | 占比 | 文件名 |
+|------|--------|------|--------|
+| 训练集 | 186,619 | 77.62% | train.csv |
+| 验证集 | 31,086 | 12.93% | val.csv |
+| 测试集 | 22,721 | 9.45% | test.csv |
+| **总计** | **240,426** | **100%** | |
+
+## 情感分布
+
+### 训练集情感分布 (186,619条)
+
+| 情感 | 样本数 | 占比 |
+|------|--------|------|
+| neutral | 95,392 | 51.12% |
+| joy | 40,380 | 21.64% |
+| sadness | 14,886 | 7.98% |
+| anger | 11,142 | 5.97% |
+| fear | 11,011 | 5.90% |
+| surprise | 9,528 | 5.11% |
+| disgust | 4,280 | 2.29% |
+
+### 验证集情感分布 (31,086条)
+
+| 情感 | 样本数 | 占比 |
+|------|--------|------|
+| neutral | 12,734 | 40.96% |
+| joy | 7,509 | 24.15% |
+| sadness | 2,915 | 9.38% |
+| fear | 2,506 | 8.06% |
+| anger | 2,329 | 7.49% |
+| surprise | 2,196 | 7.06% |
+| disgust | 897 | 2.89% |
+
+### 测试集情感分布 (22,721条)
+
+| 情感 | 样本数 | 占比 |
+|------|--------|------|
+| neutral | 10,249 | 45.11% |
+| joy | 5,198 | 22.88% |
+| sadness | 2,074 | 9.13% |
+| anger | 1,729 | 7.61% |
+| fear | 1,516 | 6.67% |
+| surprise | 1,348 | 5.93% |
+| disgust | 607 | 2.67% |
+
+### 整体情感分布 (240,426条)
+
+| 情感 | 样本数 | 占比 |
+|------|--------|------|
+| neutral | 118,375 | 49.24% |
+| joy | 53,087 | 22.08% |
+| sadness | 19,875 | 8.27% |
+| anger | 15,200 | 6.32% |
+| fear | 15,033 | 6.25% |
+| surprise | 13,072 | 5.44% |
+| disgust | 5,784 | 2.41% |
+
+## 数据源分布
+
+### 训练集数据源分布
+
+| 数据源 | 样本数 | 占比 |
+|--------|--------|------|
+| dailydialog | 87,170 | 46.71% |
+| goemotions | 41,251 | 22.10% |
+| tweetemotions | 21,763 | 11.66% |
+| mteb_emotion | 15,956 | 8.55% |
+| meld | 9,989 | 5.35% |
+| Movies_Reviews | 6,725 | 3.60% |
+| isear | 3,765 | 2.02% |
+
+### 验证集数据源分布
+
+| 数据源 | 样本数 | 占比 |
+|--------|--------|------|
+| goemotions | 11,786 | 37.91% |
+| dailydialog | 8,069 | 25.95% |
+| tweetemotions | 6,218 | 20.00% |
+| mteb_emotion | 1,988 | 6.39% |
+| meld | 1,109 | 3.57% |
+| isear | 1,076 | 3.46% |
+| Movies_Reviews | 840 | 2.70% |
+
+### 测试集数据源分布
+
+| 数据源 | 样本数 | 占比 |
+|--------|--------|------|
+| dailydialog | 7,740 | 34.06% |
+| goemotions | 5,893 | 25.94% |
+| tweetemotions | 3,110 | 13.69% |
+| meld | 2,610 | 11.49% |
+| mteb_emotion | 1,986 | 8.74% |
+| Movies_Reviews | 842 | 3.71% |
+| isear | 540 | 2.38% |
+
+## 数据源信息
+
+### Movies_Reviews
+- **特点**: 电影评论情感数据
+- **覆盖**: 包含7种情感类别
+
+### DailyDialog
+- **特点**: 真实对话数据，包含多轮对话
+- **覆盖**: 包含7种情感类别
+
+### GoEmotions
+- **特点**: Reddit评论数据，口语化表达
+- **覆盖**: 包含7种情感类别
+
+### ISEAR
+- **特点**: 国际情感研究数据，高质量文本
+- **覆盖**: 包含7种情感类别
+
+### MELD
+- **特点**: 多模态情感对话数据，来自电视剧《老友记》
+- **覆盖**: 包含7种情感类别
+
+### mteb_emotion
+- **特点**: 情感分析数据集，包含多种情感表达
+- **覆盖**: 包含7种情感类别
+
+### Tweet Emotions
+- **特点**: Twitter推文数据，包含@mentions
+- **覆盖**: 包含7种情感类别
+
+## 数据质量说明
+
+1. **类别不平衡**: neutral占主导（约40-51%），disgust样本最少（约2-3%）
+2. **多源数据融合**: 7个数据源的文本已合并，每个样本包含`source`字段标识来源
+3. **情感类别**: 统一使用7种Ekman情感类别，确保标签一致性
+4. **数据分割**: 按7:2:1比例分割为训练集、验证集和测试集
+5. **缺失值**: 已过滤所有缺失值，训练集、验证集和测试集均无缺失值
+
+## 情感类别定义
+
+- **neutral**: 中性，无情感倾向
+- **joy**: 快乐，愉悦
+- **sadness**: 悲伤，难过
+- **anger**: 愤怒，生气
+- **fear**: 恐惧，害怕
+- **surprise**: 惊讶，意外
+- **disgust**: 厌恶，反感
+
+## 使用建议
+
+1. **类别不平衡处理**: 建议使用类别权重或过采样/欠采样技术处理类别不平衡问题
+2. **数据增强**: 对于样本较少的类别（如disgust），可以考虑数据增强技术
+3. **多源数据融合**: 不同数据源的文本风格差异较大，建议在训练时注意数据分布
+4. **评估指标**: 由于类别不平衡，建议使用F1-score、precision、recall等指标，而非仅使用准确率
+5. **缺失值处理**: 训练前建议处理数据中的缺失值
+
+## 文件结构
+
+```
+dataset_huggingface_enhance/
+├── train.csv              # 合并后的训练集（186,619条）
+├── val.csv                # 合并后的验证集（31,086条）
+├── test.csv               # 合并后的测试集（22,721条）
+├── label_list.txt         # 情感标签列表
+├── info.md                # 数据集统计信息
+├── README.md              # 数据集说明文档
+├── stats.py               # 数据集统计脚本
+└── dataset_infos.json     # Hugging Face数据集配置
+```
+
+## 数据格式
+
+所有CSV文件包含以下列：
+- `text`: 文本内容
+- `label_text`: 情感标签（neutral/joy/sadness/anger/fear/surprise/disgust）
+- `source`: 数据来源（如goemotions、dailydialog等）
+
+---
+
+*生成时间: 2026-01-07*
+*数据版本: v2*
+*数据源: 7个Ekman情感数据集合并*

label_list.txt

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+- anger  # 愤怒    
+- disgust # 厌恶   
+- joy # 快乐       
+- sadness # 悲伤   
+- fear # 恐惧     
+- surprise # 惊讶   
+- neutral # 中性   

train/train.csv

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