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---
language:
- en
size_categories:
- 100K<n<1M
task_categories:
- text-generation
- text-classification
task_ids:
- dialogue-generation
pretty_name: Reddit Constructive Conversations
dataset_info:
features:
- name: sdid
dtype: string
- name: text
dtype: string
config_name: default
download_size: 864000000
dataset_size: 864000000
tags:
- reddit
- constructive-dialogue
- conversations
- social-media
- discourse-analysis
- high-quality
- curated
license: other
---
# Reddit Constructive Conversations
A curated collection of **802,066 constructive conversations** from Reddit. This dataset contains only the constructive discussions filtered from a larger corpus.
## Dataset Description
This dataset contains Reddit conversations that have been identified as constructive through automated classification. Each sample represents a multi-author discussion thread that demonstrates positive discourse patterns like respectful disagreement, information sharing, collaborative problem-solving, and constructive engagement.
### Key Features
- **High Quality**: Only constructive conversations (filtered from 1.4M samples)
- **Substantial Scale**: 802,066 conversation examples
- **Efficient Format**: Clean JSON with just essential fields
- **Multi-Domain**: Reddit discussions across diverse topics
- **Research Ready**: Perfect for studying positive online discourse
- **Training Ready**: Ideal for training dialogue systems and conversation models
## Dataset Structure
### Data Fields
- **`sdid`** (string): Unique sample identifier for the Reddit discussion
- **`text`** (string): Multi-author conversation text with anonymized author markers (`[author0]`, `[author1]`, etc.)
### Data Format
```json
{
"sdid": "fp43zz2",
"text": "[author0] This is a great discussion starter. [author1] I agree, and here's some additional context that might be helpful..."
}
```
## Usage
### Loading the Dataset
```python
from datasets import load_dataset
import json
# Option 1: Using Hugging Face datasets
dataset = load_dataset("NiklasKoch/reddit-constructive")
# Option 2: Load directly from JSONL
conversations = []
with open('reddit_threads_constructive.jsonl', 'r', encoding='utf-8') as f:
for line in f:
conversations.append(json.loads(line))
print(f"Loaded {len(conversations)} constructive conversations")
print(f"First example: {conversations[0]}")
```
## Limitations and Considerations
### Data Limitations
- **Platform-Specific**: Reflects Reddit's culture and user demographics
- **Time-Bound**: Conversations from May 2020
- **English Only**: No multilingual coverage
- **Automated Selection**: Based on model predictions, not human annotation
- **Context Removal**: Individual threads extracted from broader discussions
### Bias Considerations
- **Platform Bias**: Reddit users may not represent general population
- **Topic Bias**: Some subjects may be over/under-represented
- **Model Bias**: Selection reflects training model's understanding of "constructive"
## Ethical Considerations
### Responsible Use
- Dataset intended for research and educational purposes
- Users should consider platform-specific biases
- Human oversight recommended for production applications
## Dataset Creation
This dataset was created by:
1. Starting with 1.4M Reddit conversations from the **Pushshift Reddit dataset** (https://archive.org/download/pushshift_reddit_200506_to_202212/)
2. Using a trained classification model (https://huggingface.co/NiklasKoch/qwen-discussion-classifier) to identify constructive discussions
3. Filtering for high-confidence constructive predictions (prediction = 1.0)
4. Retaining only essential fields (`sdid`, `text`) for clean format
5. Anonymizing all usernames with generic author markers
6. Quality validation and sample verification
**Source Data**: Public Reddit discussions collected by Pushshift (May 2020)
**Model Source**: https://github.com/Niklas257/Reddit-Constructiveness-Classification.git
**Processing**: Automated classification and quality filtering
**Result**: 802,066 high-quality constructive conversations (56.3% of original dataset)
## License
**Custom License - Academic/Research Use Only - Non-Commercial**
This dataset contains data originally from the Pushshift Reddit dataset, which is subject to Reddit's Terms of Service and Pushshift's data use policies. The dataset is provided for academic and research purposes only.
### Terms of Use
1. **Underlying Reddit Data**: The Reddit posts and comments included in this dataset are sourced from the Pushshift Reddit dataset. This data remains subject to:
- Reddit's Terms of Service and API Terms
- Pushshift's original data sharing terms
- **Non-commercial use only**
- Academic and research purposes only
2. **Annotations**: The annotations added to this dataset are provided under the **Creative Commons Attribution 4.0 International License (CC-BY-4.0)**. You are free to:
- Share and adapt the annotations
- Provide appropriate credit
- Indicate if changes were made
## Dataset Card Authors
Niklas Koch, Georg August University of Göttingen
## Dataset Card Contact
niklas.koch01@stud.uni-goettingen.de |