A collection of papers, implementations, datasets, and tools for deep and non-deep community detection.
- Awesome Deep Community Detection
- Survey
- Convolutional Networks-based Community Detection
- Graph Attention Network-based Community Detection
- Generative Adversarial Network-based Community Detection
- Autoencoder-based Community Detection
- Other Deep Learning-based Community Detection
- Non-Deep Learning-based Communtiy Detection
- Datasets
- Tools
| Paper Title | Venue | Year | Materials |
|---|---|---|---|
| A comprehensive survey on community detection with deep learning | IEEE TNNLS | 2022 | [Paper] [Report] [Supplementary] |
| A survey of community detection approaches: From statistical modeling to deep learning | IEEE TKDE | 2021 | [Paper] |
| Deep learning for community detection: Progress, challenges and opportunities | IJCAI | 2020 | [Paper] [Report] |
| A survey of community detection methods in multilayer networks | Data Min. Knowl. Discov. | 2020 | [Paper] |
| Community detection in node-attributed social networks: A survey | Comput. Sci. Rev. | 2020 | [Paper] |
| Community detection in networks: A multidisciplinary review | J. Netw. Comput. Appl. | 2018 | [Paper] |
| Community discovery in dynamic networks: A survey | ACM Comput. Surv. | 2018 | [Paper] |
| Evolutionary computation for community detection in networks: A review | IEEE TEVC | 2018 | [Paper] |
| Metrics for community analysis: A survey | ACM Comput. Surv. | 2017 | [Paper] |
| Network community detection: A review and visual survey | Preprint | 2017 | [Paper] |
| Community detection in networks: A user guide | Phys. Rep. | 2016 | [Paper] |
| Community detection in social networks | WIREs Data Min. Knowl. Discov. | 2016 | [Paper] |
| Overlapping community detection in networks: The state-of-the-art and comparative study | ACM Comput. Surv. | 2013 | [Paper] |
| Clustering and community detection in directed networks: A survey | Phys. Rep. | 2013 | [Paper] |
| Community detection in graphs | Phys. Rep. | 2010 | [Paper] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| Inductive representation learning via CNN for partially-unseen attributed networks | IEEE TNSE | 2021 | IEPAN | [Paper] |
| A deep learning approach for semi-supervised community detection in online social networks | Knowl.-Based Syst. | 2021 | SparseConv2D | [Paper] |
| Edge classification based on convolutional neural networks for community detection in complex network | Physica A | 2020 | ComNet-R | [Paper] |
| A deep learning based community detection approach | SAC | 2019 | SparseConv | [Paper] |
| Deep community detection in topologically incomplete networks | Physica A | 2017 | Xin et al. | [Paper] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| Complex exponential graph convolutional networks | Inf. Sci. | 2023 | CEGCN | [Paper] [Code] |
| Community detection based on community perspective and graph convolutional network | Expert Syst. Appl. | 2023 | CPGC | [Paper] |
| Heterogeneous question answering community detection based on graph neural network | Inf. Sci. | 2023 | HCDBG | [Paper] |
| Overlapping community detection on complex networks with graph convolutional networks | Comput. Commun. | 2023 | CDMG | [Paper] |
| Deep MinCut: Learning node embeddings from detecting communities | Pattern Recognit. | 2022 | DMC | [Paper] |
| End-to-end modularity-based community co-partition in bipartite networks | CIKM | 2022 | BiCoN+GCN | [Paper] |
| CLARE: A semi-supervised community detection algorithm | KDD | 2022 | CLARE | [Paper] [Code] |
| Efficient graph convolution for joint node representation learning and clustering | WSDM | 2022 | GCC | [Paper] [Code] |
| Geometric graph representation learning via maximizing rate reduction | WWW | 2022 | [Paper] [Code] | |
| RepBin: Constraint-based graph representation learning for metagenomic binning | AAAI | 2022 | RepBin | [Paper] [Code] |
| SSSNET: Semi-supervised signed network clustering | SDM | 2022 | SSSNET | [Paper] [Code] |
| Learning Guarantees for Graph Convolutional Networks on The Stochastic Block Model | ICLR | 2022 | GCN-SBM | [Paper] |
| When convolutional network meets temporal heterogeneous graphs: An effective community detection method | IEEE TKDE | 2021 | THGCN | [Paper] |
| Multi-view contrastive graph clustering | NIPS | 2021 | MCGC | [paper] [Code] |
| Graph debiased contrastive learning with joint representation clustering | IJCAI | 2021 | Zhao et al. | [Paper] |
| Spectral embedding network for attributed graph clustering | Neural Netw. | 2021 | SENet | [Paper] |
| Unsupervised learning for community detection in attributed networks based on graph convolutional network | Neurocomputing | 2021 | SGCN | [Paper] |
| Adaptive graph encoder for attributed graph embedding | KDD | 2020 | AGE | [Paper][Code] |
| CommDGI: Community detection oriented deep graph infomax | CIKM | 2020 | CommDGI | [Paper] |
| Going deep: Graph convolutional ladder-shape networks | AAAI | 2020 | GCLN | [Paper] |
| Independence promoted graph disentangled networks | AAAI | 2020 | IPGDN | [Paper] |
| Supervised community detection with line graph neural networks | ICLR | 2019 | LGNN | [Paper][Code] |
| Graph convolutional networks meet Markov random fields: Semi-supervised community detection in attribute networks | AAAI | 2019 | MRFasGCN | [Paper] |
| Overlapping community detection with graph neural networks | DLG Workshop, KDD | 2019 | NOCD | [Paper][Code] |
| Attributed graph clustering via adaptive graph convolution | IJCAI | 2019 | AGC | [Paper][Code] |
| CayleyNets: Graph convolutional neural networks with complex rational spectral filters | IEEE TSP | 2019 | CayleyNets | [Paper][Code] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| CSAT: Contrastive sampling-aggregating transformer for community detection in attribute-missing networks | IEEE TCSS | 2023 | CSAT | [Paper] |
| A graph-enhanced attention model for community detection in multiplex networks | Expert Syst. Appl. | 2023 | GEAM | [Paper][Code] |
| Hierarchical attention network for attributed community detection of joint representation | Neural Comput. Appl. | 2022 | HiAN | [Paper] |
| Detecting communities from heterogeneous graphs: A context path-based graph neural network model | CIKM | 2021 | CP-GNN | [Paper][Code] |
| HDMI: High-order deep multiplex infomax | WWW | 2021 | HDMI | [Paper][Code] |
| Self-supervised heterogeneous graph neural network with co-contrastive learning | KDD | 2021 | HeCo | [Paper][Code] |
| Unsupervised attributed multiplex network embedding | AAAI | 2020 | DMGI | [Paper][Code] |
| MAGNN: Metapath aggregated graph neural network for heterogeneous graph embedding | WWW | 2020 | MAGNN | [Paper] [Code] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| CANE: Community-aware network embedding via adversarial training | Knowl. Inf. Syst. | 2021 | CANE | [Paper] |
| Self-training enhanced: Network embedding and overlapping community detection with adversarial learning | IEEE TNNLS | 2021 | ACNE ACNE-ST |
[Paper] |
| Adversarial Learning of Balanced Triangles for Accurate Community Detection on Signed Networks | ICDM | 2021 | ABC | [Paper] |
| SEAL: Learning heuristics for community detection with generative adversarial networks | KDD | 2020 | SEAL | [Paper][Code] |
| Multi-class imbalanced graph convolutional network learning | IJCAI | 2020 | DR-GCN | [Paper] |
| JANE: Jointly adversarial network embedding | IJCAI | 2020 | JANE | [Paper] |
| ProGAN: Network embedding via proximity generative adversarial network | KDD | 2019 | ProGAN | [Paper] |
| CommunityGAN: Community detection with generative adversarial nets | WWW | 2019 | CommunityGAN | [Paper][Code] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| A graph convolutional fusion model for community detection in multiplex networks | Data Min. Knowl. Discov. | 2023 | GCFM | [Paper] |
| A novel network core structure extraction algorithm utilized variational autoencoder for community detection | Expert Syst. Appl. | 2023 | CSEA | [Paper][Code] |
| Community detection based on unsupervised attributed network embedding | Expert Syst. Appl. | 2023 | CDBNE | [Paper][Code] |
| Exploring temporal community structure via network embedding | IEEE TCYB | 2022 | VGRGMM | [Paper] |
| Graph community infomax | ACM TKDD | 2022 | GCI | [Paper] |
| Multi-modal non-Euclidean brain network analysis with community detection and convolutional autoencoder | IEEE TETCI | 2022 | M2CDCA | [Paper] |
| Deep neighbor-aware embedding for node clustering in attributed graphs | Pattern Recognit. | 2022 | DNENC | [Paper] |
| Semi-supervised overlapping community detection in attributed graph with graph convolutional autoencoder | Inf. Sci. | 2022 | SSGCAE | [Paper] |
| A weighted network community detection algorithm based on deep learning | Appl. Math. Comput. | 2021 | WCD | [Paper] |
| DNC: A deep neural network-based clustering-oriented network embedding algorithm | J. Netw. Comput. Appl. | 2021 | DNC | [Paper] |
| Boosting nonnegative matrix factorization based community detection with graph attention auto-encoder | IEEE TBD | 2021 | NMFGAAE | [Paper] |
| Self-supervised graph convolutional network for multi-view clustering | IEEE TMM | 2021 | SGCMC | [Paper] |
| Graph embedding clustering: Graph attention auto-encoder with cluster-specificity distribution | Neural Netw. | 2021 | GEC-CSD | [Paper][Code] |
| An evolutionary autoencoder for dynamic community detection | Sci. China Inf. Sci. | 2020 | sE-Autoencoder | [Paper] |
| Stacked autoencoder-based community detection method via an ensemble clustering framework | Inf. Sci. | 2020 | CDMEC | [Paper] |
| Community-centric graph convolutional network for unsupervised community detection | IJCAI | 2020 | GUCD | [Paper] |
| Structural deep clustering network | WWW | 2020 | SDCN | [Paper][Code] |
| One2Multi graph autoencoder for multi-view graph clustering | WWW | 2020 | One2Multi | [Paper][Code] |
| Multi-view attribute graph convolution networks for clustering | IJCAI | 2020 | MAGCN | [Paper] |
| Deep multi-graph clustering via attentive cross-graph association | WSDM | 2020 | DMGC | [Paper][Code] |
| Effective decoding in graph auto-encoder using triadic closure | AAAI | 2020 | TGA TVGA |
[Paper] |
| Graph representation learning via ladder gamma variational autoencoders | AAAI | 2020 | LGVG | [Paper] |
| High-performance community detection in social networks using a deep transitive autoencoder | Inf. Sci. | 2019 | Transfer-CDDTA | [Paper] |
| Attributed graph clustering: A deep attentional embedding approach | IJCAI | 2019 | DAEGC | [Paper] |
| Stochastic blockmodels meet graph neural networks | ICML | 2019 | DGLFRM | [Paper][Code] |
| Variational graph embedding and clustering with laplacian eigenmaps | IJCAI | 2019 | VGECLE | [Paper] |
| Optimizing variational graph autoencoder for community detection | BigData | 2019 | VGAECD-OPT | [Paper] |
| Integrative network embedding via deep joint reconstruction | IJCAI | 2018 | UWMNE | [Paper] |
| Deep attributed network embedding | IJCAI | 2018 | DANE | [Paper][Code] |
| Deep network embedding for graph representation learning in signed networks | IEEE TCYB | 2018 | DNE-SBP | [Paper][Code] |
| DFuzzy: A deep learning-based fuzzy clustering model for large graphs | Knowl. Inf. Syst. | 2018 | DFuzzy | [Paper] |
| Learning community structure with variational autoencoder | ICDM | 2018 | VGAECD | [Paper] |
| Adversarially regularized graph autoencoder for graph embedding | IJCAI | 2018 | ARGA ARVGA |
[Paper][Code] |
| BL-MNE: Emerging heterogeneous social network embedding through broad learning with aligned autoencoder | ICDM | 2017 | DIME | [Paper][Code] |
| MGAE: Marginalized graph autoencoder for graph clustering | CIKM | 2017 | MGAE | [Paper][Code] |
| Graph clustering with dynamic embedding | Preprint | 2017 | GRACE | [Paper] |
| Modularity based community detection with deep learning | IJCAI | 2016 | semi-DRN | [Paper][Code] |
| Deep neural networks for learning graph representations | AAAI | 2016 | DNGR | [Paper] |
| Learning deep representations for graph clustering | AAAI | 2014 | GraphEncoder | [Paper][Code] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| Contrastive deep nonnegative matrix factorization for community detection | ICASSP | 2024 | CDNMF | [Paper][Code] |
| A hyperbolic approach for learning communities on graphs | Data Min. Knowl. Discov. | 2023 | RComE | [Paper][Code] |
| Deep alternating non-negative matrix factorisation | Knowl.-Based Syst. | 2022 | DA-NMF | [Paper] |
| CGC: Contrastive Graph Clustering for Community Detection and Tracking | WWW | 2022 | CGC | [Paper] |
| Deep graph clustering via dual correlation reduction | AAAI | 2022 | DCRN | [Paper] [Code] |
| Cluster-aware heterogeneous information network embedding | WSDM | 2022 | VaCA-HINE | [Paper] |
| Graph filter-based multi-view attributed graph clustering | IJCAI | 2021 | MvAGC | [Paper] [Code] |
| A deep learning framework for self-evolving hierarchical community detection | CIKM | 2021 | ReinCom | [Paper] |
| Unsupervised learning of joint embeddings for node representation and community detection | ECML-PKDD | 2021 | J-ENC | [Paper] |
| Community detection based on modularized deep nonnegative matrix factorization | Int. J. Pattern Recognit. Artif. Intell. | 2020 | MDNMF | [Paper] |
| Deep autoencoder-like nonnegative matrix factorization for community detection | CIKM | 2018 | DANMF | [Paper][Code] |
| Community discovery in networks with deep sparse filtering | Pattern Recognit. | 2018 | DSFCD | [Paper] |
| A non-negative symmetric encoder-decoder approach for community detection | CIKM | 2017 | Sun et al. | [Paper] |
| Paper Title | Venue | Year | Method | Materials |
|---|---|---|---|---|
| CataBEEM: Integrating latent interaction categories in node-wise community detection models for network data | ICML | 2023 | CataBEEM | [Paper][Code] |
| Nonnegative matrix factorization based on node centrality for community detection | ACM TKDD | 2023 | NCNMF | [Paper][Code] |
| Dual structural consistency preserving community detection on social networks | IEEE TKDE | 2023 | DSCPCD | [Paper][Code] |
| Symmetry and graph bi-regularized non-negative matrix factorization for precise community detection | IEEE TASAE | 2023 | B-NMF | [Paper] |
| Multi-view metro station clustering based on passenger flows: A functional data-edged network community detection approach | Data Min. Knowl. Discov. | 2023 | F2MVNCD | [Paper] |
| Multiplex network community detection algorithm based on motif awareness | Knowl.-Based Syst. | 2023 | CDMA | [Paper] |
| Community detection via autoencoder-like nonnegative tensor decomposition | IEEE TNNLS | 2022 | ANTD | [Paper] |
| Graph regularized nonnegative matrix factorization for community detection in attributed networks | IEEE TNSE | 2022 | AGNMF-AN | [Paper] |
| Modeling and detecting communities in node attributed networks | IEEE TKDE | 2022 | CRSBM | [Paper] |
| The trade-off between topology and content in community detection: An adaptive encoder-decoder-based NMF approach | Expert Syst. Appl. | 2022 | ANMF | [Paper] |
| Community detection in subspace of attribute | Inf. Sci. | 2022 | SOA | [Paper] |
| Explainability in graph data science: Interpretability, replicability, and reproducibility of community detection | IEEE Signal Process. Mag. | 2022 | -- | [Paper] |
| Differentially private community detection for stochastic block models | ICML | 2022 | Seif et al. | [Paper] |
| Community detection in multiplex networks based on evolutionary multi-task optimization and evolutionary clustering ensemble | IEEE TEVC | 2022 | BSMCD | [Paper] |
| Fine-grained attributed graph clustering | SDM | 2022 | FGC | [Paper] [Code] |
| HB-DSBM: Modeling the dynamic complex networks from community level to node level | IEEE TNNLS | 2022 | HB-DSBM | [Paper] |
| PMCDM: Privacy-preserving multiresolution community detection in multiplex networks | Knowl.-Based Syst. | 2022 | PMCDM | [Paper] |
| Rearranging 'indivisible' blocks for community detection | IEEE TKDE | 2022 | RaidB | [Paper] |
| Information diffusion-aware likelihood maximization optimization for community detection | Inf. Sci. | 2022 | EM-CD L-Louvain |
[Paper] |
| Community detection in partially observable social networks | ACM TKDD | 2022 | KroMFac | [Paper] |
| Diverse and experienced group discovery via hypergraph clustering | SDM | 2022 | Amburg et al. | [Paper] [Code] |
| Community detection in graph: An embedding method | IEEE TNSE | 2022 | SENMF | [Paper] |
| Community detection using local group assimilation | Expert Syst. Appl. | 2022 | LGA | [Paper] |
| Identifying Early Warning Signals from News Using Network Community Detection | AAAI | 2022 | Le Vine et al. | [Paper] |
| Residual2Vec: Debiasing graph embedding with random graphs | NIPS | 2021 | residual2vec | [Paper] [Code] |
| Streaming belief propagation for community detection | NIPS | 2021 | StSBM | [Paper] |
| Triangle-aware spectral sparsifiers and community detection | KDD | 2021 | Sotiropoulos et al. | [Paper] [Code] |
| Self-guided community detection on networks with missing edges | IJCAI | 2021 | SGCD | [Paper] |
| Effective and scalable clustering on massive attributed graphs | WWW | 2021 | ACMin | [Paper] [Code] |
| Scalable Community Detection via Parallel Correlation Clustering | VLDB | 2021 | Shi et al. | [Paper] [Code] |
| Proximity-based group formation game model for community detection in social network | Knowl.-Based Syst. | 2021 | PBCD | [Paper] |
| When random initializations help: A study of variational inference for community detection | J. Mach. Learn. Res. | 2021 | BCAVI | [Paper] |
| Compactness preserving community computation via a network generative process | IEEE TETCI | 2021 | FCOCD | [Paper] |
| Identification of communities with multi-semantics via bayesian generative model | IEEE TBD | 2021 | ICMS | [Paper] |
| A network embedding-enhanced Bayesian model for generalized community detection in complex networks | Inf. Sci. | 2021 | NEGCD | [Paper] |
| Multi-objective evolutionary clustering for large-scale dynamic community detection | Inf. Sci. | 2021 | DYN-MODPSO | [Paper] |
| A joint community detection model: Integrating directed and undirected probabilistic graphical models via factor graph with attention mechanism | IEEE TBD | 2021 | AdaMRF | [Paper] |
| SimClusters: Community-based representations for heterogeneous recommendations at Twitter | KDD | 2020 | SimClusters | [Paper] [Code] |
| Evolutionary markov dynamics for network community detection | IEEE TKDE | 2020 | ePMCL | [Paper] |
| A network reduction-based multiobjective evolutionary algorithm for community detection in large-scale complex networks | IEEE TCYB | 2020 | RMOEA | [Paper] |
| Integrating group homophily and individual personality of topics can better model network communities | ICDM | 2020 | GHIPT | [Paper] |
| Community preserving network embedding based on memetic algorithm | IEEE TETCI | 2020 | MemeRep | [Paper] |
| Detecting the evolving community structure in dynamic social networks | World Wide Web J. | 2020 | DECS | [Paper] [Code] |
| EdMot: An edge enhancement approach for motif-aware community detection | KDD | 2019 | EdMot | [Paper] |
| LPANNI: Overlapping community detection using label propagation in large-scale complex networks | IEEE TKDE | 2019 | LPANNI | [Paper] |
| Detecting prosumer-community groups in smart grids from the multiagent perspective | IEEE TSMC | 2019 | PVMAS | [Paper] |
| Local community mining on distributed and dynamic networks from a multiagent perspective | IEEE TCYB | 2016 | AOCCM | [Paper] |
| General optimization technique for high-quality community detection in complex networks | Phys. Rev. E | 2014 | Combo | [Paper] |
| Spectral methods for community detection and graph partitioning | Phys. Rev. E | 2013 | -- | [Paper] |
| Stochastic blockmodels and community structure in networks | Phys. Rev. E | 2011 | DCSBM | [Paper] |
- Citeseer, Cora, Pubmed https://linqs.soe.ucsc.edu/data
- DBLP http://snap.stanford.edu/data/com-DBLP.html
- Chemistry, Computer Science, Medicine, Engineering http://kddcup2016.azurewebsites.net/
- Facebook http://snap.stanford.edu/data/ego-Facebook.html
- Epinions http://www.epinions.com/
- Youtube http://snap.stanford.edu/data/com-Youtube.html
- Last.fm https://www.last.fm/
- LiveJournal http://snap.stanford.edu/data/soc-LiveJournal1.html
- Gplus http://snap.stanford.edu/data/ego-Gplus.html
- Cellphone Calls http://www.cs.umd.edu/hcil/VASTchallenge08/
- Enron Mail http://www.cs.cmu.edu/~enron/
- Friendship https://dl.acm.org/doi/10.1145/2501654.2501657
- Rados http://networkrepository.com/ia-radoslaw-email.php
- Karate, Football, Dolphin http://www-personal.umich.edu/~mejn/netdata/
- Internet http://www-personal.umich.edu/~mejn/netdata/
- Java https://github.com/gephi/gephi/wiki/Datasets
- Hypertext http://www.sociopatterns.org/datasets
- Gephi https://gephi.org/
- Pajek http://mrvar.fdv.uni-lj.si/pajek/
- LFR https://www.santofortunato.net/resources
Disclaimer
If you have any questions, please feel free to contact us. Emails: fanzhen.liu@hdr.mq.edu.au, xing.su2@hdr.mq.edu.au