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Li, Tianyi; Zhang, Pan1
Self-falsifiable hierarchical detection of overlapping communities on social networks
Source PublicationNEW JOURNAL OF PHYSICS
Language英语
KeywordCOMPLEX NETWORKS NODES
AbstractNo community detection algorithm can be optimal for all possible networks, thus it is important to identify whether the algorithm is suitable for a given network. We propose a multi-step algorithmic solution scheme for overlapping community detection based on an advanced label propagation process, which imitates the community formation process on social networks. Our algorithm is parameter-free and is able to reveal the hierarchical order of communities in the graph. The unique property of our solution scheme is self-falsifiability; an automatic quality check of the results is conducted after the detection, and the fitness of the algorithm for the specific network is reported. Extensive experiments show that our algorithm is self-consistent, reliable on networks of a wide range of size and different sorts, and is more robust than existing algorithms on both sparse and large-scale social networks. Results further suggest that our solution scheme may uncover features of networks' intrinsic community structures.
2020
ISSN1367-2630
Volume22Issue:3Pages:33014
Cooperation Status国际
Subject AreaPhysics
MOST Discipline CataloguePhysics, Multidisciplinary
DOI10.1088/1367-2630/ab73ca
Indexed BySCIE
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Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/27087
CollectionSCI期刊论文
Affiliation1.MIT, Syst Dynam Grp, Sloan Sch Management, Cambridge, MA 02139 USA
2.Chinese Acad Sci, CAS Key Lab Theoret Phys, Inst Theoret Phys, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Li, Tianyi,Zhang, Pan. Self-falsifiable hierarchical detection of overlapping communities on social networks[J]. NEW JOURNAL OF PHYSICS,2020,22(3):33014.
APA Li, Tianyi,&Zhang, Pan.(2020).Self-falsifiable hierarchical detection of overlapping communities on social networks.NEW JOURNAL OF PHYSICS,22(3),33014.
MLA Li, Tianyi,et al."Self-falsifiable hierarchical detection of overlapping communities on social networks".NEW JOURNAL OF PHYSICS 22.3(2020):33014.
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