README.md

---
dataset_info:
- config_name: full
  features:
  - name: text
    dtype: string
  - name: class
    dtype: string
  - name: source_url
    dtype: string
  - name: source_type
    dtype: string
  - name: likes
    dtype: int64
  - name: comments
    dtype: int64
  - name: reposts
    dtype: int64
  - name: views
    dtype: int64
  - name: date
    dtype: string
  - name: post_id
    dtype: int64
  - name: label
    dtype: int64
  - name: engagement_total
    dtype: int64
  - name: engagement_rate
    dtype: float64
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  - name: validation
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  - name: test
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    num_examples: 5681
  - name: full
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    num_examples: 56805
  download_size: 39622234
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- config_name: simple
  features:
  - name: text
    dtype: string
  - name: class
    dtype: string
  - name: label
    dtype: int64
  splits:
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  - name: validation
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    num_examples: 5680
  - name: test
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    num_examples: 5681
  - name: full
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  download_size: 35709543
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configs:
- config_name: full
  data_files:
  - split: train
    path: full/train-*
  - split: validation
    path: full/validation-*
  - split: test
    path: full/test-*
  - split: full
    path: full/full-*
- config_name: simple
  data_files:
  - split: train
    path: simple/train-*
  - split: validation
    path: simple/validation-*
  - split: test
    path: simple/test-*
  - split: full
    path: simple/full-*
license: mit
task_categories:
- text-classification
- token-classification
- zero-shot-classification
- text-generation
- summarization
language:
- tt
pretty_name: 'VK Groups: Tatar Social Media Dataset'
---

# VK Groups Dataset: Tatar Social Media Posts

## Dataset Description

This dataset contains posts from five popular VKontakte (VK) communities targeting Tatar-speaking audiences. It includes content across different themes: religion, relationships, humor, advice, and cooking. The dataset is designed for various NLP tasks including text classification, sentiment analysis, topic modeling, and engagement prediction.

- **Curated by:** TatarNLPWorld
- **Language(s):** Tatar (Cyrillic script), some Russian code-switching
- **License:** MIT

### Dataset Sources

- **Repository:** https://huggingface.co/datasets/TatarNLPWorld/vk-groups
- **Source VK Groups:**
  - Религия (Religion): https://vk.com/allahtan
  - Ялгыз Тушәк (Lonely Bed/Relationships): https://vk.com/ialgyz16
  - Сазлык (Swamp/Humor): https://vk.com/public147862424
  - КИҢӘШ КИРӘК (Advice Needed): https://vk.com/sovet_kinesh
  - Кулинария (Cooking): https://vk.com/public221151764

## Dataset Summary

| Statistic | Value |
|-----------|-------|
| Total posts | 56,805 |
| Total classes | 5 |
| Date range | 2015-06-17 to 2026-03-11 |
| Total likes | 2,708,506 |
| Total views | 344,348,797 |
| Average engagement rate | 40.17% |

### Class Distribution

| Class | Count | Percentage |
|-------|-------|------------|
| Сазлык (Humor) | 22,040 | 38.8% |
| Религия (Religion) | 13,017 | 22.9% |
| КИҢӘШ КИРӘК (Advice) | 10,187 | 17.9% |
| Ялгыз Тушәк (Relationships) | 9,688 | 17.1% |
| Кулинария (Cooking) | 1,873 | 3.3% |

## Dataset Structure

Two configurations are available:

### 1. `full` - Complete dataset with all features
- `text`: Post content (string)
- `class`: Class name in Tatar (string)
- `source_url`: URL of the source VK group (string)
- `source_type`: Always "vk_group" (string)
- `likes`: Number of likes (int64)
- `comments`: Number of comments (int64)
- `reposts`: Number of reposts (int64)
- `views`: Number of views (int64)
- `date`: Post publication date (string)
- `post_id`: Unique post identifier (int64)
- `label`: Numeric class label (0-4) (int64)
- `engagement_total`: Total interactions (likes+comments+reposts) (int64)
- `engagement_rate`: (engagement_total / views) * 100 (float64)

### 2. `simple` - Simplified version for classification
- `text`: Post content (string)
- `class`: Class name in Tatar (string)
- `label`: Numeric class label (0-4) (int64)

### Data Splits

All configurations are split into:

| Split | Size | Percentage |
|-------|------|------------|
| Train | 45,444 | 80% |
| Validation | 5,680 | 10% |
| Test | 5,681 | 10% |
| Full | 56,805 | 100% |
| Sample | 1,000 | 1.8% |

## Dataset Creation

### Data Collection

Posts were collected from five public VK communities using the VK API. The data includes all publicly available posts from each group's inception through March 2026.

### Data Processing

1. Raw posts were extracted with metadata (likes, comments, reposts, views, date)
2. Empty or invalid posts (length < 10 characters) were removed
3. Duplicate posts were deduplicated
4. Posts consisting only of special characters/links were filtered out
5. Final dataset: 56,805 posts (from original 117,831, 48.2% retained)

### Label Mapping

| Label | Class |
|-------|-------|
| 0 | КИҢӘШ КИРӘК (Advice) |
| 1 | Кулинария (Cooking) |
| 2 | Религия (Religion) |
| 3 | Сазлык (Humor) |
| 4 | Ялгыз Тушәк (Relationships) |

## Uses

### Direct Use

- **Text Classification**: Multi-class classification of Tatar social media content
- **Sentiment Analysis**: Analyze emotional tone across different community types
- **Topic Modeling**: Discover themes in Tatar-language social media
- **Engagement Prediction**: Predict post popularity based on content
- **Code-switching Analysis**: Study Tatar-Russian language mixing
- **Cultural Studies**: Research Tatar online communities and discourse

### Out-of-Scope Use

- Not suitable for training production systems without careful bias evaluation
- Not representative of all Tatar speakers or online communities
- Contains user-generated content with potential biases

## Bias, Risks, and Limitations

1. **Class imbalance**: Cooking class (3.3%) is significantly underrepresented
2. **Platform bias**: Only VKontakte, may not represent other social media
3. **Language variation**: Mix of Tatar and Russian may affect model performance
4. **Temporal bias**: 10+ years of data, language use may have evolved
5. **Content bias**: Topics reflect community interests, not general Tatar discourse

## Citation

If you use this dataset, please cite:

@dataset{vk_groups_tatar_2026,
  title = {VK Groups Dataset: Tatar Social Media Posts},
  author = {Arabov, Mullosharaf Kurbonovich and TatarNLPWorld},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/TatarNLPWorld/vk-groups},
  note = {Created by Arabov Mullosharaf Kurbonovich for TatarNLPWorld organization}
}

## How to Use

```python
from datasets import load_dataset

# Load full dataset
dataset_full = load_dataset('TatarNLPWorld/vk-groups', 'full')
train_full = dataset_full['train']

# Load simple dataset (for classification)
dataset_simple = load_dataset('TatarNLPWorld/vk-groups', 'simple')
train_simple = dataset_simple['train']

# Access data
texts = train_simple['text']
labels = train_simple['label']
classes = train_simple['class']
```

## Contact

For questions or collaborations, please contact TatarNLPWorld.

---

**Languages:** Tatar (Cyrillic), some Russian  
**License:** MIT  
**Size:** 56,805 posts  
**Last Updated:** March 2026