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Reddit Mental Health Risk Classification Dataset
Dataset Summary
This dataset is a curated mental health text classification dataset designed for training Natural Language Processing (NLP) models to identify different levels of mental health risk from social media posts.
The dataset was created by combining and preprocessing two publicly available Kaggle datasets:
- Sentiment Analysis for Mental Health
- Suicidal Tweet Detection Dataset
The original datasets were cleaned, filtered, relabeled, and merged to create a unified three-class mental health risk classification dataset.
Dataset Sources
1. Sentiment Analysis for Mental Health
Source: https://www.kaggle.com/datasets/suchintikasarkar/sentiment-analysis-for-mental-health
This dataset contains mental health-related statements labeled with multiple mental health categories including:
- Depression
- Anxiety
- Stress
- Bipolar Disorder
- Personality Disorder
- Suicidal
- Normal
It aggregates and cleans data from several publicly available mental health datasets, making it suitable for research and machine learning applications.
2. Suicidal Tweet Detection Dataset
Source: https://www.kaggle.com/datasets/aunanya875/suicidal-tweet-detection-dataset
This dataset consists of annotated tweets for suicidal ideation detection and binary classification of suicidal versus non-suicidal content.
Dataset Construction
The final dataset was created through the following pipeline:
- Combined both source datasets.
- Removed duplicate samples.
- Removed missing and invalid records.
- Standardized text formatting.
- Unified label schema.
- Mapped the original labels into three risk categories.
Label Mapping
The final dataset contains three classes:
| Label | Risk Level | Description |
|---|---|---|
| 0 | High Risk | Explicit suicidal ideation, suicide planning, self-harm intent, or immediate crisis. |
| 1 | Low Risk | General discussions, emotionally neutral posts, or non-crisis mental health conversations. |
| 2 | Moderate Risk | Depression, anxiety, emotional distress, hopelessness, stress, or substance abuse without explicit suicidal intent. |
Dataset Statistics
- Total Samples: 47,894
- Number of Classes: 3
| Class | Samples |
|---|---|
| High Risk | 12,064 |
| Moderate Risk | 19,487 |
| Low Risk | 16,343 |
Dataset Format
The dataset consists of two columns:
| Column | Description |
|---|---|
| statement | Text of the social media post |
| status | Integer class label |
Example:
| statement | status |
|---|---|
| I don't think I can keep fighting anymore. | 0 |
| I've been feeling anxious for months. | 2 |
| I had a wonderful day with my friends. | 1 |
Intended Uses
This dataset is intended for:
- Mental health risk classification
- NLP research
- Text classification
- Transformer model fine-tuning
- Mental health AI research
- Educational and academic purposes
Limitations
- The dataset is derived from publicly available social media text and may not represent the broader population.
- Labels are intended for research purposes and should not be interpreted as clinical diagnoses.
- Models trained on this dataset should not be used as the sole basis for medical or emergency decisions.
Ethical Considerations
This dataset contains discussions related to depression, anxiety, emotional distress, and suicidal ideation. It is intended exclusively for research, educational, and machine learning purposes.
Users should ensure that any models trained using this dataset are deployed responsibly and include appropriate human oversight for real-world applications.
Citation
If you use this dataset in your research, please cite both the original dataset creators and this processed version.
Original Datasets
Sentiment Analysis for Mental Health: https://www.kaggle.com/datasets/suchintikasarkar/sentiment-analysis-for-mental-health
Suicidal Tweet Detection Dataset: https://www.kaggle.com/datasets/aunanya875/suicidal-tweet-detection-dataset
License
Please refer to the licenses of the original Kaggle datasets. This repository contains a processed and relabeled version of publicly available data intended for research and educational use.
Acknowledgements
This dataset was prepared as part of the Google Summer of Code (GSoC) 2026 project under HumanAI. We gratefully acknowledge the creators of the original Kaggle datasets for making their work publicly available to support mental health research and NLP development.
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