Community detection has become a key issue in the field of complex network analysis, which essentially involves dividing the network into groups or communities, where nodes within the same community exhibit more dense connections than nodes outside their community. However, most existing label propagation methods are not stable enough. To this end, this paper proposes a community detection algorithm based on node importance. Firstly, node importance is calculated based on neighbor similarity. Then, label update order is rearranged based on node importance. Finally, label propagation is performed by combining node importance and label update order. The experimental results show that the proposed algorithm has more stable community partitioning results, and its modularity and standard normalization indicators have good performance.
Key words
community detection /
complex network /
node importance /
label propagation
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