NiklasKoch/reddit-constructive

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

{
  "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

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)

Dataset Card Authors

Niklas Koch, Georg August University of Göttingen

Dataset Card Contact

niklas.koch01@stud.uni-goettingen.de