metadata
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.