Line graphs of weighted networks for overlapping communities

被引:95
作者
Evans, T. S. [1 ,2 ]
Lambiotte, R. [1 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Inst Math Sci, London SW7 2PG, England
[2] Univ London Imperial Coll Sci Technol & Med, London SW7 2AZ, England
关键词
Random Walk; Adjacency Matrix; Line Graph; Weighted Graph; Incidence Matrix;
D O I
10.1140/epjb/e2010-00261-8
中图分类号
O469 [凝聚态物理学];
学科分类号
070205 ;
摘要
In this paper, we develop the idea to partition the edges of a weighted graph in order to uncover overlapping communities of its nodes. Our approach is based on the construction of different types of weighted line graphs, i.e. graphs whose nodes are the links of the original graph, that encapsulate differently the relations between the edges. Weighted line graphs are argued to provide an alternative, valuable representation of the system's topology, and are shown to have important applications in community detection, as the usual node partition of a line graph naturally leads to an edge partition of the original graph. This identification allows us to use traditional partitioning methods in order to address the long-standing problem of the detection of overlapping communities. We apply it to the analysis of different social and geographical networks.
引用
收藏
页码:265 / 272
页数:8
相关论文
共 46 条
[1]   Link communities reveal multiscale complexity in networks [J].
Ahn, Yong-Yeol ;
Bagrow, James P. ;
Lehmann, Sune .
NATURE, 2010, 466 (7307) :761-U11
[2]   Graph-based methods for analysing networks in cell biology [J].
Aittokallio, Tero ;
Schwikowski, Benno .
BRIEFINGS IN BIOINFORMATICS, 2006, 7 (03) :243-255
[3]  
[Anonymous], 1960, Rend. Circolo Mat. Palermo, DOI DOI 10.1007/BF02854581
[4]  
[Anonymous], 1978, Selected Topics in Graph Theory
[5]  
[Anonymous], GECCO 09
[6]  
[Anonymous], CHIN PHYS LETT
[7]  
[Anonymous], 2006, Physical review letters
[8]  
[Anonymous], ARXIV08121770
[9]  
[Anonymous], 1993, The Stanford graph base: A platform for combinatorial computing
[10]  
[Anonymous], SPRINGER METHODOS SE