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Web Authority Signals
Train trust and authority models on 43T backlinks, referring domain graphs, and link intelligence.
Product answers:
- How does authority flow across the web?
- What makes a domain credible to AI systems?
This product is for:
- AI engineers building trust scoring systems
- Data scientists training entity linking models
- ML teams enriching knowledge graphs with topical authority signals
Built to solve:
- Training trust models on incomplete graph data
- Missing access to a wide backlink corpus needed for model accuracy
- No signal to separate credible domains from low-quality ones
What's inside
- 43T backlink corpus for model training
- Referring domain graph structure
- Authority Score labels for trust modeling
- Anchor text semantics for entity linking
- Topical link categories for knowledge graph enrichment
- Historical link velocity signals
Coverage & scale
Api methods
Backlinks Overview
This report provides a summary of backlinks, including their type, referring domains, and IP addresses for a domain, root domain, or URL.
Backlinks
This report lists backlinks for a domain, root domain, or URL.
Backlinks Historical
This report returns only monthly historical trends of multiple backlinks and referring domains for the queried domain. When you run a query for a domain, in return, in each line, you receive a date (Unix timestamp) and the number of backlinks and referring domains the queried domain had at that time. Results are sorted by date from the most recent to the oldest.
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Our backlink crawler scans more than 17 billion web pages every day to discover new backlinks.
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