The clustering coefficient and community structure of bipartite networks
arXiv:0710.0117 · doi:10.1016/j.physa.2008.09.006
Abstract
Many real-world networks display a natural bipartite structure. It is necessary and important to study the bipartite networks by using the bipartite structure of the data. Here we propose a modification of the clustering coefficient given by the fraction of cycles with size four in bipartite networks. Then we compare the two definitions in a special graph, and the results show that the modification one is better to character the network. Next we define a edge-clustering coefficient of bipartite networks to detect the community structure in original bipartite networks.
9 pages, 4 figures
References in corpus (20)
- Statistical mechanics of complex networks
- The structure and function of complex networks
- Community structure in social and biological networks
- Uncovering the overlapping community structure of complex networks in nature and society
- The diameter of the world wide web
- Hierarchical organization of modularity in metabolic networks
- Defining and identifying communities in networks
- Community detection in complex networks using Extremal Optimization
- Self-similar community structure in organisations
- Community Structure in Jazz
- Modularity and community detection in bipartite networks
- Module identification in bipartite and directed networks
- Cycles and clustering in bipartite networks
- Structure and Time-Evolution of an Internet Dating Community
- Uncovering collective listening habits and music genres in bipartite networks
- Clustering and Synchronization of Oscillator Networks
- Human Sexual Contact Network as a Bipartite Graph
- Email as Spectroscopy: Automated Discovery of Community Structure within Organizations
- Basic Notions for the Analysis of Large Affiliation Networks / Bipartite Graphs
- Construction of bipartite and unipartite weighted networks from collections of journal papers
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