Our Methodology
Transparency in how we process, and analyze data to deliver actionable insights.
Analysis Methods
Theme Extraction
We use natural language processing (NLP) and clustering algorithms to identify recurring themes within subreddit content. Our AI models analyze post titles, keywords, and contextual relationships to surface the most discussed topics.
Engagement Scoring
Posts are scored based on multiple factors including upvote ratios, comment velocity, and relative performance compared to subreddit averages. This helps identify what content truly resonates with each community.
Timing Analysis
By analyzing thousands of posts per community, we calculate optimal posting windows. Our algorithm considers timezone distributions, historical engagement patterns, and day-of-week variations.
Similarity Detection
We identify related subreddits through user overlap analysis, shared vocabulary, and topic similarity. This helps you discover adjacent communities for cross-promotion or audience expansion.
Data Freshness
Our infrastructure continuously ingests new data, ensuring that your analysis reflects the most recent community trends. Historical data is retained for trend comparison and pattern detection.
Privacy & Transparency
We are committed to responsible data practices and transparency in our methodology.
Our Commitments:
- Public data only - We never access private subreddits or direct messages
- No PII storage - Usernames and personal data are not retained
- Aggregated insights - All analytics are based on aggregate patterns
Questions? Contact us at [email protected] for any methodology or privacy questions.
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