---
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype: string
  splits:
  - name: original
    num_bytes: 21409
    num_examples: 105
  - name: augmented
    num_bytes: 198556
    num_examples: 1050
  download_size: 69405
  dataset_size: 219965
configs:
- config_name: default
  data_files:
  - split: original
    path: data/original-*
  - split: augmented
    path: data/augmented-*
---

## Dataset Summary
This dataset contains **YouTube comments** collected from videos of different music styles.  
Each comment is labeled with the corresponding **music genre**. The dataset is intended for **text classification** tasks, exploring how language and sentiment vary across musical contexts.

- **Content type:** YouTube user comments  
- **Labels (genres):** `pop`, `rock`, `metal`, `classical`, `jazz`, `r&b`, `electrical`  
- **Task type:** Text Classification (multi-class)  
- **Goal:** Predict the music genre based on comment content  


## Data Splits
- No predefined train/test split.  
- Users can apply their own strategy (e.g., 80/20 split, stratified sampling).  



## Intended Uses
- **Multi-class Text Classification:** Predict genre labels from comments.  
- **NLP & Sentiment Analysis:** Explore how musical genres shape user language.  
- **Educational Use:** Demonstrates building labeled datasets from real-world social media sources.