| --- |
| language: |
| - ms |
| size_categories: |
| - 1K<n<10K |
| pretty_name: Cyberbully Dataset for Bahasa Malaysia |
| --- |
| # Dataset Card for MYBully |
|
|
| MYBully is a manually and HITL-annotated dataset of social media posts in Bahasa Malaysia (with some code-mixed English), designed for multiple text classification tasks including cyberbullying detection, hate speech detection, sentiment analysis, and emotion recognition. |
|
|
| ## Uses |
|
|
| - Training and evaluation of classification models for cyberbullying detection. |
| - Benchmarking multitask NLP models for low-resource languages (Malay). |
| - Cross-task learning (transfer from sentiment/emotion to bullying-related tasks). |
|
|
| ## Dataset Structure |
| 1. Instances: 4,680 tweets |
| - 2,687 manually annotated |
| - 1,993 annotated via Human-in-the-Loop (HITL) strategy |
|
|
| 2. Tasks: |
| - Cyberbullying (binary/multi-label) |
| - Hate Speech (binary) |
| - Sentiment (positive/neutral/negative) |
| - Emotion (e.g., anger, joy, sadness, fear, neutral) |
|
|
| 3. Each instance includes: |
| - Tweet |
| - Sentiment: *Positive, Negative or Neutral* |
| - Emotion: *Anger, Disgust, Neutral, Sadness, Fear, Surprise, Happiness* |
| - Bully: *Yes, No* |
| - Hate: *Yes, No* |
| - anno_type (To indicate, if record is Manually Annotated or HITL-Based Annotation): *manual, hitl* |
| *More details will be shared soon* |
| |
| ```bibtex |
| @misc{mohan_raj_2026, |
| author = {Mohan Raj and Manjeevan Singh Seera }, |
| title = {MYBully}, |
| year = 2026, |
| url = {https://huggingface.co/datasets/mohanrj/MYBully }, |
| doi = {10.57967/hf/8021 }, |
| publisher = {Hugging Face }, |
| howpublished = {\url{https://huggingface.co/datasets/mohanrj/MYBully}} |
| } |
| ``` |
