Triangular clustering in document networks

Abstract

Document networks are characteristic in that a document node, e.g. a webpage or an article, carries meaningful content. Properties of document networks are not only affected by topological connectivity between nodes, but also strongly influenced by the semantic relation between content of the nodes. We observe that document networks have a large number of triangles and a high value of clustering coefficient. And there is a strong correlation between the probability of formation of a triangle and the content similarity among the three nodes involved. We propose the degree-similarity product (DSP) model which well reproduces these properties. The model achieves this by using a preferential attachment mechanism which favours the linkage between nodes that are both popular and similar. This work is a step forward towards a better understanding of the structure and evolution of document networks.

10 pages, 3 figures, 2 tables

References in corpus (10)

• Emergence of scaling in random networks
• Statistical mechanics of complex networks
• The structure and function of complex networks
• Clustering in Complex Directed Networks
• Are randomly grown graphs really random?
• Emergence of communities in weighted networks
• A Model for Social Networks
• Clustering in complex networks. I. General formalism
• Motif-based communities in complex networks
• Characterising Web Site Link Structure

Cited by in corpus (11)

• Quantifying and identifying the overlapping community structure in networks
• Potential Theory for Directed Networks
• Spectral methods for the detection of network community structure: a comparative analysis
• Bridgeness: A Local Index on Edge Significance in Maintaining Global Connectivity
• Exploring the structural regularities in networks
• Uncovering the community structure associated with the diffusion dynamics of networks
• Covariance, correlation matrix and the multi-scale community structure of networks
• Modeling the clustering in citation networks
• Distinguishing manipulated stocks via trading network analysis
• Link power coordination for energy conservation in complex communication networks
• Modeling citation networks based on vigorousness and dormancy