Methodology
How we collect, verify, and present data across 2 million entities.
The Knowledge Graph
DropThe maintains a structured knowledge graph — a database of entities (people, movies, series, games, companies, cryptocurrencies, countries, cities) and the relationships between them.
Every entity page on the site is backed by this graph. When you visit a page about a director, you see which movies they directed, which actors they worked with, and which production companies distributed their work. That's not editorial guesswork — it's graph data.
Data Sources
Every data point in the knowledge graph traces back to a verifiable source. We pull from official APIs, open knowledge bases, regulatory filings, and structured public datasets across these categories:
Structured, machine-readable records for biographical data, demographics, filmography, and geography.
Movie, series, and anime metadata: cast, crew, ratings, posters, release dates, streaming availability.
Company financials, revenue, officer data. Direct from regulatory bodies and market data providers.
Real-time and historical pricing for cryptocurrencies and equities: market cap, volume, price ranges.
Country and city-level data: GDP, population, growth rates, demographic breakdowns.
Real-world search and view data used for entity scoring and content prioritization. No synthetic metrics.
No scraped blog posts. No unattributed estimates. Every source is an official API or public dataset.
Entity Scoring
Not all entities are equal. We use two scoring systems to determine how entities are prioritized.
Wikipedia Popularity Tiers
Each entity is assigned a tier (S, A, B, C, or D) based on actual Wikipedia pageview data — not opinion, not editorial judgment. Tier S entities receive the most Wikipedia views globally; Tier D the fewest.
These tiers determine which entities get indexed, which appear in sitemaps, and which receive priority in content creation. The goal is simple: allocate coverage where public interest actually exists.
Entity Richness Score
A composite score measuring data completeness for each entity: how many fields are populated, link density within the knowledge graph, and media availability (images, streaming data, financial records). Higher richness means better entity pages.
How Articles Are Produced
Articles start with data, not opinion. The process:
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Data First
Entity data and cross-references from the knowledge graph form the foundation. The article is structured around verified facts before any editorial layer is added.
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AI-Assisted Writing
Content is generated with AI assistance. This is fully disclosed on our transparency page.
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Internal Linking
Each article contains 10-20+ internal entity links connecting back to the knowledge graph. These aren't decorative — they're structural references to real data.
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Standard Format
Every article includes: a Quick Answer, a TLDR summary, an editorial take (clearly labeled as opinion), FAQ, and cited sources.
For full details on our AI disclosure and editorial personas, see Transparency.
Data Freshness
Stale data is worse than no data. Here's how we keep things current:
- Entity data — Enriched and updated on rolling cycles. New entities are added as they emerge in source databases.
- Financial data — Stock prices and cryptocurrency values updated regularly via API feeds from Yahoo Finance and CoinGecko.
- Streaming catalog — Streaming availability tracked across major platforms, refreshed periodically to reflect catalog changes.
- Articles — Timestamped at publication. Updated when new data emerges or corrections are needed.
What We Don't Do
We don't invent statistics or present estimates as facts. Every number comes from a source.
We analyze published data, specifications, and reviews. We don't claim hands-on experience we don't have.
Rankings and entity placement are determined by data, not sponsorship. Advertising is always disclosed.
Our AI-assisted process is disclosed. See Transparency for full details.
Feedback
Found an error in our data? Have a correction? Contact us at editor@dropthe.org or use our contact page.
"Data is only useful when it's accurate. Help us keep it that way."