ReDepress Dataset
Note: To access this dataset please fill the ReDepress_agreement.docx document and send an email to [email protected]
The ReDepress Dataset originates from the paper
"ReDepress: A Cognitive Framework for Detecting Depression Relapse from Social Media".
This dataset is designed to support research on detecting depression relapse using social media text.
It provides rich temporal user data and cognitive bias annotations, allowing systems to monitor conversational dynamics and make timely inferences.
Overview
- Total Users: 204
- File Format:
.parquet
files (one per user) - Ground Truth File:
ground_truth_labels.csv
- agreement to access dataset:
ReDepress_agreement.docx
Each user is assigned a binary label in the ground_truth_labels.csv
file:
0
→ No Relapse1
→ Relapse
The dataset contains two categories of users:
- Relapsed Users
- Non-relapsed Users
Each user file includes a chronological sequence of posts, containing the user’s own submissions.
Data Structure
1. User Files (.parquet
)
Each user file contains the following fields:
Column | Description |
---|---|
post_id |
Unique string identifier for the post |
author |
Anonymous identifier of the user who created the post |
date |
ISO 8601 timestamp of post creation |
selftext |
Main content (body text) of the submission |
title |
Title summarizing the submission |
avg_attention_bias |
Mean of all three annotators’ attention bias scores |
avg_interpretation_bias |
Mean of all three annotators’ interpretation bias scores |
avg_memory_bias |
Mean of all three annotators’ memory bias scores |
avg_rumination |
Mean of all three annotators’ rumination bias scores |
majority_attention_bias |
Majority label for attention bias |
majority_interpretation_bias |
Majority label for interpretation bias |
majority_memory_bias |
Majority label for memory bias |
majority_rumination |
Majority label for rumination bias |
2. Label Mapping
The majority label for each cognitive bias was mapped to numerical values as follows:
Memory Bias
Label | Mapped Value |
---|---|
Positive | 1 |
Negative | -1 |
No Bias | 0 |
Attention Bias
Label | Mapped Value |
---|---|
Positive | 1 |
Negative | -1 |
No Bias | 0 |
Interpretation Bias
Label | Mapped Value |
---|---|
Positive | 1 |
Negative | -1 |
No Bias | 0 |
Rumination
Label | Mapped Value |
---|---|
Reflection | 1 |
Brooding | -1 |
No Rumination | 0 |
Ground Truth Labels
The ground_truth_labels.csv
file contains the final gold standard relapse annotations:
Column | Description |
---|---|
author |
Anonymous user identifier |
relapse_label |
0 for no relapse, 1 for relapse |
Use Cases
Researchers can use this dataset to:
- Train and evaluate relapse detection models based on text data.
- Study cognitive bias patterns preceding depression relapse.
- Analyze temporal evolution of users’ social media language and behavior.
Citation
If you use this dataset in your research, please cite:
ReDepress: A Cognitive Framework for Detecting Depression Relapse from Social Media
https://arxiv.org/pdf/2509.17991
Ethical Considerations
- All user data is anonymized to protect privacy.
- The dataset must be used solely for research purposes related to mental health, language, and computational social science.
- Researchers are encouraged to handle the data with sensitivity and adhere to ethical AI and mental health research guidelines.
License
To access this dataset please fill the ReDepress_agreement.docx document and send an email to [email protected]
Contact
For questions or collaboration inquiries, please refer to the contact information provided in the ReDepress paper.
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