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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2011
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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 |
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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 |
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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. |
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KWAK, Haewoon EOM, Young-Ho CHOI, Yoonchan JEONG, Hawoong |
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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 |
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Institutional Knowledge at Singapore Management University |
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2011 |
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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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