# aditya-grover/node2vec

Repository: https://github.com/aditya-grover/node2vec
Canonical: https://ross.abutalabs.com/products/node2vec
Homepage: http://snap.stanford.edu/node2vec/
Language: Scala
License: MIT
License Family: permissive
Last push: 2022-07-21T14:37:25+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3718, "days_push": 1504, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2739, forks 906 (observed 2026-08-28T04:07:16.414421+00:00)

## What it is
Reference implementation of the node2vec algorithm for learning continuous low-dimensional node representations from arbitrary (un)directed, (un)weighted graphs via biased random walks. It outputs embeddings usable as features for downstream machine learning tasks.

## Use cases
- learn node embeddings from a graph
- generate features for network machine learning
- detect communities in a network
- embed a social graph for classification
- run node2vec on an edgelist
- graph representation learning for link prediction

## When to choose
- you need the original reference implementation of node2vec for research or citation
- you have graph data in edgelist format and want node feature vectors
- you want to balance homophily vs structural equivalence via p and q parameters

## When to avoid
- you need high performance on very large graphs - use the SNAP C++ implementation instead
- you need actively maintained code with modern Python packaging
- you want deep graph neural networks rather than random-walk embeddings

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science
- domain: machine-learning, graph-processing
- platform: python, cross-platform
- tags: graph-embeddings, node2vec, network-embedding, random-walks, snap, algorithms

## Member repositories
- aditya-grover/node2vec (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:16.414421+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:19:11.435228+00:00, confidence not recorded.
  - readme: https://github.com/aditya-grover/node2vec (fetched 2026-08-28T04:07:16.414421+00:00, sha 66dc025bc4e4)
  - homepage: http://snap.stanford.edu/node2vec/ (fetched 2026-08-29T09:57:20.901913+00:00, sha 582c785e4176)
  - site_page: http://snap.stanford.edu/about.html (fetched 2026-08-29T09:57:20.910861+00:00, sha 3a6fe0b68395)
- Data as of 2026-08-30T08:39:29.467469+00:00.