Reddit Post Discussion Classifier Performance Across Three Subreddits

Performance metrics for a binary classifier predicting whether a Reddit post will spark a discussion. The dataset, shared by Cara Lynch on figshare, contains results from models trained on reconstructed threads from r/politics, r/CryptoCurrency, and r/Conspiracy. It was last updated in May 2026.

Use Cases

• Predicting discussion initiation on social media based on post features like linked domain and author activity.
• Comparing feature importance for thread growth across different online communities like r/politics and r/CryptoCurrency.
• Training interpretable models for content moderation using SHAP analysis on textual and semantic features.
• Analyzing how community context moderates the effect of features like source novelty on discussion scale.

Strengths

• Model results are based on a concise, interpretable feature set designed for transparency.
• Analysis covers three distinct subreddit communities (r/politics, r/CryptoCurrency, r/Conspiracy) for comparative insights.
• The dataset is small (5.5 KB) and shared under a permissive CC-BY-4.0 license.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset's scope is limited to three specific subreddits, which may affect generalizability.

Provenance

Source

figshare

Collection Method

Results from training subreddit-specific classifiers on reconstructed Reddit threads.

Freshness

Last updated 2026-05-14 17:34:39; freshness should be verified.