# 20 years of network community detection

arXiv: https://arxiv.org/abs/2208.00111 · HTML: https://mlsanity.com/paper/2208.00111/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 40 references that are in the map.
- First posted on arXiv 30 Jul 2022.

## Builds on (most cited first, 9 of 9)

- [Inductive Representation Learning on Large Graphs](https://mlsanity.com/paper/1706.02216/) (2017)
- [Graph Embedding Techniques, Applications, and Performance: A Survey](https://mlsanity.com/paper/1705.02801/) (2017)
- [Community detection thresholds and the weak Ramanujan property](https://mlsanity.com/paper/1311.3085/) (2013)
- [The ground truth about metadata and community detection in networks](https://mlsanity.com/paper/1608.05878/) (2016)
- [Hierarchical Block Structures and High-resolution Model Selection in Large Networks](https://mlsanity.com/paper/1310.4377/) (2013)
- [Structure and inference in annotated networks](https://mlsanity.com/paper/1507.04001/) (2015)
- [Community detection in networks: Structural communities versus ground truth](https://mlsanity.com/paper/1406.0146/) (2014)
- [Generalized communities in networks](https://mlsanity.com/paper/1505.07478/) (2015)
- [Structure and dynamics of core-periphery networks](https://mlsanity.com/paper/1309.6928/) (2013)

## Built on by (most cited first, 23 of 23)

- [Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity](https://mlsanity.com/paper/2209.04562/) (2022)
- [Bipartite mixed membership distribution-free model. A novel model for community detection in overlapping bipartite weighted networks](https://mlsanity.com/paper/2211.00912/) (2022)
- [Analyzing Modularity Maximization in Approximation, Heuristic, and Graph Neural Network Algorithms for Community Detection](https://mlsanity.com/paper/2310.10898/) (2023)
- [Implicit models, latent compression, intrinsic biases, and cheap lunches in community detection](https://mlsanity.com/paper/2210.09186/) (2022)
- [Heuristic Modularity Maximization Algorithms for Community Detection Rarely Return an Optimal Partition or Anything Similar](https://mlsanity.com/paper/2302.14698/) (2023)
- [The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks](https://mlsanity.com/paper/2310.01144/) (2023)
- [Towards Faster Graph Partitioning via Pre-training and Inductive Inference](https://mlsanity.com/paper/2409.00670/) (2024)
- [Efficient Identity and Position Graph Embedding via Spectral-Based Random Feature Aggregation](https://mlsanity.com/paper/2505.20992/) (2025)
- [Optimal community detection in dense bipartite graphs](https://mlsanity.com/paper/2505.18372/) (2025)
- [InfraredGP: Efficient Graph Partitioning via Spectral Graph Neural Networks with Negative Corrections](https://mlsanity.com/paper/2508.19737/) (2025)
- [Trading off Quality for Efficiency of Community Detection: An Inductive Method across Graphs](https://mlsanity.com/paper/2209.14825/) (2022)
- [Community detection in complex networks via node similarity, graph representation learning, and hierarchical clustering](https://mlsanity.com/paper/2303.12212/) (2023)
- [Superpixels algorithms through network community detection](https://mlsanity.com/paper/2308.14101/) (2023)
- [Multi-order Graph Clustering with Adaptive Node-level Weight Learning](https://mlsanity.com/paper/2405.12183/) (2024)
- [Topology of Syntax Networks across Languages](https://mlsanity.com/paper/2503.06724/) (2025)
- [Robust Markov stability for community detection at a scale learned based on the structure](https://mlsanity.com/paper/2504.11621/) (2025)
- [Recovering Fairness Directly from Modularity: a New Way for Fair Community Partitioning](https://mlsanity.com/paper/2505.22684/) (2025)
- [Consistent line clustering using geometric hypergraphs](https://mlsanity.com/paper/2505.24868/) (2025)
- [Effects of relational graph modularity and depth on the learning performance of neural networks](https://mlsanity.com/paper/2507.10005/) (2025)
- [Large Scale Community-Aware Network Generation](https://mlsanity.com/paper/2511.19717/) (2025)
- [Alzheimer's Disease Brain Network Mining](https://mlsanity.com/paper/2512.17276/) (2025)
- [Graph energy as a measure of community detectability in networks](https://mlsanity.com/paper/2601.05065/) (2026)
- [Topology-induced Operators Reveal Complementary Graph Representations without Training](https://mlsanity.com/paper/2609.08152/) (2026)

## Abstract (arXiv)

A fundamental technical challenge in the analysis of network data is the automated discovery of communities - groups of nodes that are strongly connected or that share similar features or roles. In this commentary we review progress in the field over the last 20 years.