Literature DB >> 16383469

Local method for detecting communities.

James P Bagrow1, Erik M Bollt.   

Abstract

We propose a method of community detection that is computationally inexpensive and possesses physical significance to a member of a social network. This method is unlike many divisive and agglomerative techniques and is local in the sense that a community can be detected within a network without requiring knowledge of the entire network. A global application of this method is also introduced. Several artificial and real-world networks, including the famous Zachary karate club, are analyzed.

Entities:  

Year:  2005        PMID: 16383469     DOI: 10.1103/PhysRevE.72.046108

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  11 in total

1.  Think locally, act locally: detection of small, medium-sized, and large communities in large networks.

Authors:  Lucas G S Jeub; Prakash Balachandran; Mason A Porter; Peter J Mucha; Michael W Mahoney
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2015-01-26

2.  Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

Authors:  István A Kovács; Robin Palotai; Máté S Szalay; Peter Csermely
Journal:  PLoS One       Date:  2010-09-02       Impact factor: 3.240

3.  Towards online multiresolution community detection in large-scale networks.

Authors:  Jianbin Huang; Heli Sun; Yaguang Liu; Qinbao Song; Tim Weninger
Journal:  PLoS One       Date:  2011-08-24       Impact factor: 3.240

4.  Discovering network structure beyond communities.

Authors:  Takashi Nishikawa; Adilson E Motter
Journal:  Sci Rep       Date:  2011-11-09       Impact factor: 4.379

5.  A DIseAse MOdule Detection (DIAMOnD) algorithm derived from a systematic analysis of connectivity patterns of disease proteins in the human interactome.

Authors:  Susan Dina Ghiassian; Jörg Menche; Albert-László Barabási
Journal:  PLoS Comput Biol       Date:  2015-04-08       Impact factor: 4.475

6.  Discovering Preferential Patterns in Sectoral Trade Networks.

Authors:  Isabella Cingolani; Carlo Piccardi; Lucia Tajoli
Journal:  PLoS One       Date:  2015-10-20       Impact factor: 3.240

7.  Correlations between community structure and link formation in complex networks.

Authors:  Zhen Liu; Jia-Lin He; Komal Kapoor; Jaideep Srivastava
Journal:  PLoS One       Date:  2013-09-06       Impact factor: 3.240

8.  NetView: a high-definition network-visualization approach to detect fine-scale population structures from genome-wide patterns of variation.

Authors:  Markus Neuditschko; Mehar S Khatkar; Herman W Raadsma
Journal:  PLoS One       Date:  2012-10-31       Impact factor: 3.240

9.  Mobile recommendation based on link community detection.

Authors:  Kun Deng; Jianpei Zhang; Jing Yang
Journal:  ScientificWorldJournal       Date:  2014-08-26

10.  Multi-resolution community detection in massive networks.

Authors:  Jihui Han; Wei Li; Weibing Deng
Journal:  Sci Rep       Date:  2016-12-13       Impact factor: 4.379

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