Graph learning· 2016
node2vec: Scalable Feature Learning for Networks
On the reading lists
- #184 in the Top 500 (2026 edition)
- #9 in Graph learning (2026 edition)
Why it matters
Introduced biased random walks balancing local and structural network information.
Condensed from the expert lists' notes.
The record
- First released
- 2016 (from arXiv 1607.00653)
- Citations
- 12,705 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.557 · computed rank 184 · consensus 0.79, must-read 0, citations percentile 0.913 (2010s · graphs), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.