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Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks
Authors:Zhi-Hao Wu  You-Fang Lin  Steve Gregory  Huai-Yu Wan  Sheng-Feng Tian
Affiliation:1. School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China
2. Department of Computer Science, University of Bristol, Bristol, BS8 1UB, U.K.
Abstract:In this paper,we propose a balanced multi-label propagation algorithm(BMLPA) for overlapping community detection in social networks.As well as its fast speed,another important advantage of our method is good stability,which other multi-label propagation algorithms,such as COPRA,lack.In BMLPA,we propose a new update strategy,which requires that community identifiers of one vertex should have balanced belonging coefficients.The advantage of this strategy is that it allows vertices to belong to any number of communities without a global limit on the largest number of community memberships,which is needed for COPRA.Also,we propose a fast method to generate "rough cores",which can be used to initialize labels for multi-label propagation algorithms,and are able to improve the quality and stability of results.Experimental results on synthetic and real social networks show that BMLPA is very efficient and effective for uncovering overlapping communities.
Keywords:overlapping community detection  multi-label propagation  social network
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