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A node influence based label propagation algorithm for community detection in networks.

Yan Xing¹, Fanrong Meng¹, Yong Zhou¹

¹School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China.

Thescientificworldjournal

|July 8, 2014

Summary

This summary is machine-generated.

We introduce a new Node Influence based Label Propagation Algorithm (NIBLPA) to improve community detection stability in large networks. NIBLPA offers more reliable results than standard LPA without sacrificing speed.

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Area of Science:

Network analysis
Data mining
Algorithm development

Background:

Label Propagation Algorithm (LPA) is a fast method for community detection in large networks.
However, LPA suffers from poor stability, limiting its practical application.
Existing methods have not adequately addressed this stability issue.

Purpose of the Study:

To propose a novel Node Influence based Label Propagation Algorithm (NIBLPA) for community detection.
To enhance the stability and performance of LPA while maintaining its efficiency.
To address the limitations of LPA's randomness in label selection and update order.

Main Methods:

Developed NIBLPA by incorporating node influence for optimized label updating order.
Introduced a refined label selection mechanism to handle ties in maximum node labels.
Evaluated NIBLPA's performance against traditional LPA and other representative methods.

Main Results:

NIBLPA demonstrates significantly improved stability compared to the standard LPA.
The algorithm maintains the high efficiency characteristic of LPA.
Experimental results on synthetic and real-world networks show superior performance over existing methods.

Conclusions:

NIBLPA effectively enhances the stability of label propagation for community detection.
The proposed method offers a robust and efficient alternative to traditional LPA.
NIBLPA provides more reliable community structures in large-scale networks.