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Constant Communities in Complex Networks

delete2013-05-10
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OA
AI
T
Tanmoy Chakraborty *
S
Sriram Srinivasan
N
Niloy Ganguly
S
Sanjukta Bhowmick
A
Animesh Mukherjee
DOI:10.1038/srep01825delete
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摘要

摘要

En 中文
Identifying community structure is a fundamental problem in network analysis. Most community detection algorithms are based on optimizing a combinatorial parameter, for example modularity. This optimization is generally NP-hard, thus merely changing the vertex order can alter their assignments to the community. However, there has been less study on how vertex ordering influences the results of the community detection algorithms. Here we identify and study the properties of invariant groups of vertices (constant communities) whose assignment to communities are, quite remarkably, not affected by vertex ordering. The percentage of constant communities can vary across different applications and based on empirical results we propose metrics to evaluate these communities. Using constant communities as a pre-processing step, one can significantly reduce the variation of the results. Finally, we present a case study on phoneme network and illustrate that constant communities, quite strikingly, form the core functional units of the larger communities.
Keyword:
DYNAMICS
AI总结

AI总结

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期刊

Scientific Reports 封面图
Scientific Reports
IF:
3.9
论文数:
27.9W
被引数:
83.5W

机构

I
indian institute of technology system (iit system)
学者数:
9.5W
论文数: 9.9W
被引数: 93
I
indian institute of technology (iit) - kharagpur
学者数:
6.2K
论文数: 6.5K
被引数: 6
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