GraphAcademy

Graph Data Science

eigenvector centrality

A centralityHow important a node is within a graph. Each centrality algorithm defines importance differently. algorithm that scores a nodeA vertex in a graph. In a property graph it can carry labels and properties. by the importance of the nodes pointing at it, so a connection to an important node counts for more than one to an unimportant one.

Lessons that use this term

The lesson and course links below open in a new tab.

3 lessons use this term. Results are ordered by term density.

Understand centrality algorithms6 mentions

  • EndorsementUnderstand centrality algorithmsCentrality, PageRank, Article Rank and HITs are the four algorithms in this4 mentions
  • Explore the graphUnderstand centrality algorithmsPage Rank Article Rank Eigenvector Centrality -1 mention
  • What is centrality?Understand centrality algorithmsGraph Data Science library provides Page Rank, Article Rank, Eigenvector Centrality and HITS as members of this1 mention

Related terms

closeness centrality
A centrality algorithm that scores a node by how few hops separate it from every other node in the graph.2 shared lessons
harmonic centrality
A closeness variant that scores a node by summing the reciprocal of the distance to every other node.2 shared lessons
betweenness centrality
A score for each node equal to how often it lies on the shortest paths between other nodes.3 shared lessons
degree centrality
A score for each node equal to its number of outgoing relationships.3 shared lessons
HITS algorithm
A link analysis algorithm that scores nodes two ways at once — as an authority, endorsed by the nodes pointing at it, and as a hub, endorsing the nodes it points to.3 shared lessons
centrality
How important a node is within a graph. Each centrality algorithm defines importance differently.2 shared lessons
bridge
A relationship whose removal disconnects the graph into two separate parts.2 shared lessons
PageRank
A centrality algorithm that scores a node by the number of nodes pointing at it and by how important those nodes are.2 shared lessons

All glossary terms