# Community structure in social and biological networks

@article{Girvan2002CommunitySI, title={Community structure in social and biological networks}, author={Michelle Girvan and Mark E. J. Newman}, journal={Proceedings of the National Academy of Sciences of the United States of America}, year={2002}, volume={99}, pages={7821 - 7826} }

A number of recent studies have focused on the statistical properties of networked systems such as social networks and the Worldwide Web. Researchers have concentrated particularly on a few properties that seem to be common to many networks: the small-world property, power-law degree distributions, and network transitivity. In this article, we highlight another property that is found in many networks, the property of community structure, in which network nodes are joined together in tightly…

## 13,053 Citations

Statistical properties of community structure in large social and information networks

- Computer ScienceWWW
- 2008

It is found that a generative model, in which new edges are added via an iterative "forest fire" burning process, is able to produce graphs exhibiting a network community structure similar to that observed in nearly every network dataset examined.

Community Detection Based on Weighted Networks

- Computer Science2008 IFIP International Conference on Network and Parallel Computing
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This paper proposes another community detecting algorithm taking into account weights of links, which turns to be especially suitable to the analysis of social and information networks.

Algorithms for discovering communities in complex networks

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This work proposes an algorithm that utilizes centrality metrics of the nodes to compute the importance of the edges in the network, and proposes a hash-table-based technique that helps to compute bibliometric similarity between nodes in O( m Δ) time.

Characterizing the Community Structure of Complex Networks

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A systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks finds that the mesoscopic organization of networks of the same category is remarkably similar.

Detecting community structure in complex networks based on a measure of information discrepancy

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- 2008

Finding Community Structure with Performance Guarantees in Scale-Free Networks

- Computer Science2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing
- 2011

It is shown, using analytical arguments, that the power-law topology indicates the presence of community structure, and an approximation algorithm for finding community structure via maximizing the modularity that guarantees optimal solutions up to a constant factor is provided.

Correlation Analysis of Nodes Identifies Real Communities in Networks

- Computer Science
- 2018

A simple and effective algorithm that uses the correlation of nodes alone, which requires neither optimization of predefined objective function nor information about the number or sizes of communities is proposed.

Structure Analysis of Email Networks by Information-Theoretic Clustering

- Computer ScienceISNN
- 2010

This paper introduces a method based on information-theoretic clustering for finding communities/modules in complex networks that is robust to the feature representation of networks and unlike most existing algorithms, does not need to search the number of communities in a network and can determine it automatically.

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