Consistent community identification in complex networks

We have found that known community identification algorithms produce inconsistent communities when the node ordering changes at input. We use the pairwise membership probability and consistency to quantify the level of consistency across multiple runs of an algorithm. Based on these two metrics, we...

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Main Authors: KWAK, Haewoon, EOM, Young-Ho, CHOI, Yoonchan, JEONG, Hawoong
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Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/5325
https://ink.library.smu.edu.sg/context/sis_research/article/6329/viewcontent/consistent_comm___PV.pdf
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spelling sg-smu-ink.sis_research-63292020-10-23T07:45:15Z Consistent community identification in complex networks KWAK, Haewoon EOM, Young-Ho CHOI, Yoonchan JEONG, Hawoong We have found that known community identification algorithms produce inconsistent communities when the node ordering changes at input. We use the pairwise membership probability and consistency to quantify the level of consistency across multiple runs of an algorithm. Based on these two metrics, we address the consistency problem without compromising the modularity. The key insight of the algorithm is to use pairwise membership probabilities as link weights. It offers a new tool in the study of community structures and their evolutions. 2011-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5325 info:doi/10.3938/jkps.59.3128 https://ink.library.smu.edu.sg/context/sis_research/article/6329/viewcontent/consistent_comm___PV.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Complex networks Community structure Modularity Databases and Information Systems OS and Networks
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Complex networks
Community structure
Modularity
Databases and Information Systems
OS and Networks
spellingShingle Complex networks
Community structure
Modularity
Databases and Information Systems
OS and Networks
KWAK, Haewoon
EOM, Young-Ho
CHOI, Yoonchan
JEONG, Hawoong
Consistent community identification in complex networks
description We have found that known community identification algorithms produce inconsistent communities when the node ordering changes at input. We use the pairwise membership probability and consistency to quantify the level of consistency across multiple runs of an algorithm. Based on these two metrics, we address the consistency problem without compromising the modularity. The key insight of the algorithm is to use pairwise membership probabilities as link weights. It offers a new tool in the study of community structures and their evolutions.
format text
author KWAK, Haewoon
EOM, Young-Ho
CHOI, Yoonchan
JEONG, Hawoong
author_facet KWAK, Haewoon
EOM, Young-Ho
CHOI, Yoonchan
JEONG, Hawoong
author_sort KWAK, Haewoon
title Consistent community identification in complex networks
title_short Consistent community identification in complex networks
title_full Consistent community identification in complex networks
title_fullStr Consistent community identification in complex networks
title_full_unstemmed Consistent community identification in complex networks
title_sort consistent community identification in complex networks
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/5325
https://ink.library.smu.edu.sg/context/sis_research/article/6329/viewcontent/consistent_comm___PV.pdf
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