Fast unfolding of communities in large networks
Origin paper
Fast unfolding of communities in large networks
Modularity and community structure in networks.
Finding and evaluating community structure in networks.
Finding community structure in very large networks.
Complex Networks
Community structure in social and biological networks
Analysis of the structure of complex networks at different resolution levels
Limited resolution and multiresolution methods in complex network community detection
Finding community structure in networks using the eigenvectors of matrices.
Computing Communities in Large Networks Using Random Walks
Comparing community structure identification
Fast algorithm for detecting community structure in networks.
When are networks truly modular
Detecting the Overlapping and Hierarchical Community Structure in Networks
A Comparison of Community Detection Algorithms on Artificial Networks
Resolution limit in community detection
A New Method for Extracting the Hierarchical Organization of Networks
A class of improved algorithms for detecting communities in complex networks
Coarse-grained diffusion distance for community structure detection in complex networks
Defining and identifying communities in networks.
On Modularity Clustering
Multiresolution community detection for megascale networks by information-based replica correlations.
The effect of size heterogeneity on community identification in complex networks
Quantitative function for community detection.
Detecting network communities by propagating labels under constraints.
Identification of overlapping community structure in complex networks using fuzzy c-means clustering
Community structure identification
Link communities reveal multiscale complexity in networks
Near linear time algorithm to detect community structures in large-scale networks.
Limits of modularity maximization in community detection
A fast and efficient heuristic algorithm for detecting community structures in complex networks
Fuzzy modularity and fuzzy community structure in networks
Unsupervised Clustering Analysis: a Multiscale Complex Networks Approach
Uncovering the overlapping community structure of complex networks in nature and society
Robustness of community structure in networks.
Detecting community structure in complex networks using simulated annealing with k-means algorithms
Improving Node Similarity for Discovering Community Structure in Complex Networks
Incremental algorithm for detecting community structure in dynamic networks
Detecting community structure in complex networks via node similarity
Covariance, correlation matrix, and the multiscale community structure of networks.
Ant Colony Optimization Based on Random Walk for Community Detection in Complex Networks: Ant Colony Optimization Based on Random Walk for Community Detection in Complex Networks
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Title | Last author  | Year | Citations | Graph references |
|---|---|---|---|---|
Community detection in graphs | S. Fortunato | 2009 | 10810 | 23 |
Community landscapes : an integrative approach to determine overlapping network module hierarchy , identify key nodes and predict network dynamics | Peter Csermely | 2010 | 0 | 22 |
Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics | Peter Csermely | 2009 | 283 | 22 |
Community landscapes : an integrative approach to determine overlapping network module hierarchy , identify key nodes and predict network dynamics | Peter Csermely | 2010 | 0 | 21 |
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions | R. D. Al-Dabbagh | 2021 | 41 | 21 |
Community detection in networks: A user guide | Darko Hric | 2016 | 1800 | 19 |
The Atlas for the Aspiring Network Scientist | M. Coscia | 2021 | 29 | 18 |
Community Structure: An Introduction | Huawei Shen | 2013 | 5 | 18 |
Modular Structure of Complex Networks | Reihaneh Rabbany Khorasgani | 2016 | 1 | 16 |
Complex information networks – detecting community structure in bipartite networks | T. Alzahrani | 2016 | 2 | 16 |
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We propose a simple method to extract the community structure of large networks. Our method is a heuristic method that is based on modularity optimization. It is shown to outperform all other known community detection methods in terms of computation time. Moreover, the quality of the communities detected is very good, as measured by the so-called modularity. This is shown first by identifying language communities in a Belgian mobile phone network of 2 million customers and by analysing a web graph of 118 million nodes and more than one billion links. The accuracy of our algorithm is also verified on ad hoc modular networks.