Awesome Community Detection

This collection links community detection research papers and their implementations.

github.com/benedekrozemberczki/awesome-communi…
Awesome Community Detection homepage screenshot

About Awesome Community Detection

Awesome Community Detection is a curated GitHub repository that collects research papers on community detection in networks, along with their implementations. It is organized into topic sections such as matrix factorization, deep learning, spectral methods, temporal methods, block models, and hypergraphs, with a separate section for libraries.

The repository is a list of references and links, not a software tool that detects communities itself. It is open source and released under the CC0 Universal license. The homepage excerpt does not state how often the list is updated or how complete it is.

Key features

  • Research papers on community detection grouped by method family
  • Topic sections including deep learning, spectral methods, and block models
  • Links to implementations alongside the listed research papers
  • A dedicated section listing software libraries
  • Tags covering graph clustering, node2vec, DeepWalk, and BigCLAM
  • Content released under the CC0 Universal license
Best for: Researchers and data scientists who want to find community detection papers and their associated code, organized by method.
Good for
  • Papers are grouped by method, which makes it easier to compare approaches
  • Listed papers are paired with implementations
  • Content is released under the CC0 Universal license
Watch out for
  • It is a curated list of links and does not perform community detection itself

Awesome Community Detection at a glance

Type
Open-source project
Pricing
Not confirmed. Check the site
Open source
Yes · Source code
Language
English
Last checked
Oct 6, 2026 · Online when checked
Listed
Oct 5, 2026

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Awesome Community Detection FAQ

What license applies to the repository?
The repository is listed under the CC0-1.0 license, also described as CC0 Universal.
Does the list include code as well as papers?
The repository describes itself as a curated list of community detection research papers with implementations, and it includes a Libraries section.
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