Centrality Scores (PageRank)
The mathematical measure of how well-connected and authoritative your brand is within search and knowledge networks.
Plain Language Definition
Centrality scores are mathematical values that measure how connected and important a specific entity is within a network of relationships. Google’s original PageRank is the most famous centrality algorithm. In knowledge graphs, centrality determines which entities are considered most authoritative — and therefore most likely to be cited by AI systems when answering related questions.
Technical Definition
Graph algorithms (PageRank, betweenness, eigenvector centrality) calculating relative node importance based on density, quality, and directionality of incoming edge connections — used in both web link graphs and entity knowledge graphs to establish authority rankings.
Why This Matters for AI Search Visibility
Your brand’s centrality in both web link graphs and knowledge graphs directly affects how authoritatively AI systems treat information about you. Building genuine inbound link relationships and knowledge graph connections increases centrality — and therefore AI citation probability.