On the reduction of instability of label propagation algorithm

Maryam Yazdani (), Ali Moeini, Mojtaba Mazoochi (), Farzaneh Rahmani () and Leila Rabiei ()
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Maryam Yazdani: Department of Algorithms and Computation, School of Engineering Science, College of Engineering, University of Tehran, Iran
Ali Moeini: Department of Algorithms and Computation, School of Engineering Science, College of Engineering, University of Tehran, Iran
Mojtaba Mazoochi: ICT Research Institute, Tehran, Iran
Farzaneh Rahmani: ICT Research Institute, Tehran, Iran
Leila Rabiei: ICT Research Institute, Tehran, Iran

International Journal of Modern Physics C (IJMPC), 2023, vol. 34, issue 04, 1-21

Abstract: Label propagation algorithm is widely used for community detection in a network due to its linear time complexity. It also does not need any predefined information such as the number of communities. However, the results of this algorithm are not stable because of the randomness strategy used in its propagation process. In this paper, a modification on label propagation strategy is proposed in which labels are propagated based on nodes importance defined by their positions and popularity among neighbors. The proposed strategy is an updating process which reduces the instability of the label propagation algorithm. Experiments on real-world and synthetic networks show that the proposed method improves accuracy in terms of modularity, NMI and ARI. Also, the method has an acceptable execution time.

Keywords: Label propagation algorithm (LPA); node importance; similarity; community detection (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0129183123500535

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