## 9,941 Citations

### Clustering and Community Detection in Directed Networks: A Survey

- Computer ScienceArXiv
- 2013

### Community Detection in Complex Networks via Clique Conductance

- Computer ScienceScientific Reports
- 2018

This paper develops a novel community-detection method based on cliques, i.e., local complete subnetworks, and shows that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

### Communities Identification Using Nodes Features

- Computer ScienceISMIS
- 2015

The main purpose of the approach is to find leader nodes of networks and to form community around those nodes and the proposed algorithm doesn’t require a priori knowledge of k number of communities to be detected.

### Graph Clustering Based on Social Network Community Detection Algorithms

- Computer Science
- 2014

The so-called walktrap algorithm aims to detect communities in graphs based on the idea that random walks tend to get trapped within communities within communities (areas with higher density of links and separated by few connections).

### Finding Statistically Significant Communities in Networks

- Computer SciencePloS one
- 2011

OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics, is presented.

### Detection of structurally homogeneous subsets in graphs

- Computer Science, MathematicsStat. Comput.
- 2014

Methods for detecting communities in undirected graphs have been recently reviewed by Fortunato and a review of methods and algorithms for detecting essentially structurally homogeneous subsets of vertices in binary or weighted and directed and undirecting graphs is made.

### Detection of structurally homogeneous subsets in graphs

- Computer Science, MathematicsStatistics and Computing
- 2013

Methods for detecting communities in undirected graphs have been recently reviewed by Fortunato and a review of methods and algorithms for detecting essentially structurally homogeneous subsets of vertices in binary or weighted and directed and undirecting graphs is made.

### A Survey on Community Detection

- Computer Science
- 2015

It has been proved that many real world networks reveal the structures of the modules or the communities that are sub graphs with more edges connecting the vertices of the same group and comparatively fewer links joining the outside vertices.

### Genetic Algorithms Approach to Community Detection

- Computer Science
- 2010

There are many versions of genetic algorithms developed for the task of community detection and here the authors concentrate on a very promising one proposed quite recently by Pizzuti, namely on genetic algorithms.

## References

SHOWING 1-10 OF 546 REFERENCES

### Community Structure in Graphs

- Computer ScienceEncyclopedia of Complexity and Systems Science
- 2009

Graph vertices are often organized into groups that seem to live fairly independently of the rest of the graph, with which they share but a few edges, whereas the relationships between group members…

### Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters

- Computer ScienceInternet Math.
- 2009

This paper employs approximation algorithms for the graph-partitioning problem to characterize as a function of size the statistical and structural properties of partitions of graphs that could plausibly be interpreted as communities, and defines the network community profile plot, which characterizes the "best" possible community—according to the conductance measure—over a wide range of size scales.

### Defining and identifying communities in networks.

- Computer ScienceProceedings of the National Academy of Sciences of the United States of America
- 2004

This article proposes a local algorithm to detect communities which outperforms the existing algorithms with respect to computational cost, keeping the same level of reliability and applies to a network of scientific collaborations, which, for its size, cannot be attacked with the usual methods.

### Finding community structure in networks using the eigenvectors of matrices.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2006

A modularity matrix plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations, and a spectral measure of bipartite structure in networks and a centrality measure that identifies vertices that occupy central positions within the communities to which they belong are proposed.

### Benchmarks for testing community detection algorithms on directed and weighted graphs with overlapping communities.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2009

The basic ideas behind the previous benchmark are extended to generate directed and weighted networks with built-in community structure, and the possibility that nodes belong to more communities is considered, a feature occurring in real systems, such as social networks.

### Finding community structure in very large networks.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2004

A hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (md log n) where d is the depth of the dendrogram describing the community structure.

### Statistical significance of communities in networks.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2010

A measure aimed at quantifying the statistical significance of single communities is defined, which is successfully applied in the case of real-world networks for the evaluation of the significance of their communities.

### Finding instabilities in the community structure of complex networks.

- Computer SciencePhysical review. E, Statistical, nonlinear, and soft matter physics
- 2005

A method to identify the nodes lying "between clusters," allowing for a general measure of the stability of the clusters, is introduced by adding noise over the edge weights.

### Discovering global network communities based on local centralities

- Computer ScienceTWEB
- 2008

A new algorithm, called ICS, is presented, which aims to discover natural network communities by inferring from the local information of nodes inherently hidden in networks based on a new centrality, that is, clusteringcentrality, which is a generalization of eigenvector centrality.