Community Detection in Dynamic Networks via Adaptive Label Propagation
November 17, 2017 Β· Declared Dead Β· π PLoS ONE
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Authors
Jihui Han, Wei Li, Longfeng Zhao, Zhu Su, Yijiang Zou, Weibing Deng
arXiv ID
1711.06535
Category
physics.soc-ph
Cross-listed
cs.SI
Citations
24
Venue
PLoS ONE
Last Checked
3 months ago
Abstract
An adaptive label propagation algorithm (ALPA) is proposed to detect and monitor communities in dynamic networks. Unlike the traditional methods by re-computing the whole community decomposition after each modification of the network, ALPA takes into account the information of historical communities and updates its solution according to the network modifications via a local label propagation process, which generally affects only a small portion of the network. This makes it respond to network changes at low computational cost. The effectiveness of ALPA has been tested on both synthetic and real-world networks, which shows that it can successfully identify and track dynamic communities. Moreover, ALPA could detect communities with high quality and accuracy compared to other methods. Therefore, being low-complexity and parameter-free, ALPA is a scalable and promising solution for some real-world applications of community detection in dynamic networks.
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