mlsanityData to 14 Oct 2026

A Comprehensive Review of Community Detection in Graphs

arXiv 2309.11798 ↗First posted 21 Sep 2023cs.SI cs.LGcited by 12

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Abstract (arXiv)

The study of complex networks has significantly advanced our understanding of community structures which serves as a crucial feature of real-world graphs. Detecting communities in graphs is a challenging problem with applications in sociology, biology, and computer science. Despite the efforts of an interdisciplinary community of scientists, a satisfactory solution to this problem has not yet been achieved. This review article delves into the topic of community detection in graphs, which serves as a thorough exposition of various community detection methods from perspectives of modularity-based method, spectral clustering, probabilistic modelling, and deep learning. Along with the methods, a new community detection method designed by us is also presented. Additionally, the performance of these methods on the datasets with and without ground truth is compared. In conclusion, this comprehensive review provides a deep understanding of community detection in graphs.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 52 of its 208 references that are in the map. First posted on arXiv 21 Sep 2023.

Builds on

52 of 208 references.

References · 52

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38 more
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  38. 2022Bayesian community detection for networks with covariatescited by 4

50 most cited of 52 All 52 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 2; 2026: 4.

12 papers.

  1. 2024CAF-YOLO: A Robust Framework for Multi-Scale Lesion Detection in Biomedical Imagerycited by 3
  2. 2024Massive Activations in Graph Neural Networks: Decoding Attention for Domain-Dependent Interpretabilitycited by 2
  3. 2025Multi-Relation Graph-Kernel Strengthen Network for Graph-Level Clusteringcited by 1
  4. 2025Topological Data Analysis for Unsupervised Anomaly Detection and Customer Segmentation on Banking Datacited by 1
  5. 2026VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detectioncited by 1
  6. 2024CCSRP: Robust Pruning of Spiking Neural Networks through Cooperative Coevolutioncited by 0
  7. 2024Case-based reasoning approach for diagnostic screening of children with developmental delayscited by 0
  8. 2024DDNet: Deformable Convolution and Dense FPN for Surface Defect Detection in Recycled Bookscited by 0
  9. 2024Wolf2Pack: The AutoFusion Framework for Dynamic Parameter Fusioncited by 0
  10. 2026Graph Neural Networks for Community Detection in Graph Signal Analysiscited by 0
  11. 2026Alcmean's: Unsupervised community detection using local Laplacian, automatic detection of the number of centerscited by 0
  12. 2026Semantic Networks as Clues: A Theoretical Foundation and Process Optimization for Semantic Network Constructioncited by 0