GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
node2vec is a Python implementation of an algorithmic framework that creates continuous feature representations for nodes in networks, useful for tasks such as link prediction and community detection.
Good fit when
- - When you are dealing with network data and require embeddings that capture the structural role of nodes rather than their content.
- - If your dataset involves complex networks where both depth-first and breadth-first traversals are important to understand node roles.
Avoid when
- - Not suitable for datasets where understanding specific node attributes is more critical than network structure itself.
- - Avoid if you only need embeddings based on shallow or flat graphs as node2vec can be computationally expensive with deeper graph explorations needed for its effectiveness.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (348d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 20, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install node2vecSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
node2vec is an algorithmic framework for learning continuous feature representations for nodes in networks. It's a process used to create embeddings suitable for tasks such as link prediction, community detection, and other network analysis tasks.
Capability facts
- Languages
- python
Source: github.language+pyproject.toml · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
Python3 implementation of the node2vec algorithm Aditya Grover, Jure Leskovec and Vid KSource link
Tags
README
Node2Vec Python3 implementation of the node2vec algorithm Aditya Grover, Jure Leskovec and Vid Kocijan. node2vec: Scalable Feature Learning for Networks. A. Grover, J. Leskovec. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. Maintenance I...
For agents
This page has a .md twin and JSON over the API.