A parametrization of generalised network clustering, in the form of four-motif prevalences, is presented. This involves three real parameters that are conditional on one-, two- and three-motif prevalences. Interpretations of these real parameters are presented that motivate a set of rewiring schemes to create appropriately clustered networks. Finally, the dynamical implications of higher order structure, as parameterised, for a contact process are considered
Graph clustering aims to identify clusters that feature tighter connections between internal nodes t...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Apart from the role the clustering coefficient plays in the definition of the small-world phenomena,...
AbstractClustering is typically measured by the ratio of triangles to all triples regardless of whet...
Clustering is typically measured by the ratio of triangles to all triples regardless of whether open...
We consider previously proposed procedures for generating clustered networks and investigate how the...
Networks have become an indispensable tool in modelling infectious diseases, with the structure of e...
Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitou...
Networks are often characterised in terms of their degree distribution and global clustering coeffic...
Networks have become an indispensable tool in modelling infectious diseases, with the structure of e...
Krueger A. Structures, processes, and clustering of complex networks. Bielefeld (Germany): Bielefeld...
We consider a procedure for generating clustered networks previously reported by Newman (M.E.J. Newm...
We consider previously proposed procedures for generating clustered networks and investigate how the...
Designing algorithms that generate networks with a given degree sequence while varying both subgraph...
Clustering is a fundamental property of complex networks and it is the mathematical expression of a ...
Graph clustering aims to identify clusters that feature tighter connections between internal nodes t...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Apart from the role the clustering coefficient plays in the definition of the small-world phenomena,...
AbstractClustering is typically measured by the ratio of triangles to all triples regardless of whet...
Clustering is typically measured by the ratio of triangles to all triples regardless of whether open...
We consider previously proposed procedures for generating clustered networks and investigate how the...
Networks have become an indispensable tool in modelling infectious diseases, with the structure of e...
Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitou...
Networks are often characterised in terms of their degree distribution and global clustering coeffic...
Networks have become an indispensable tool in modelling infectious diseases, with the structure of e...
Krueger A. Structures, processes, and clustering of complex networks. Bielefeld (Germany): Bielefeld...
We consider a procedure for generating clustered networks previously reported by Newman (M.E.J. Newm...
We consider previously proposed procedures for generating clustered networks and investigate how the...
Designing algorithms that generate networks with a given degree sequence while varying both subgraph...
Clustering is a fundamental property of complex networks and it is the mathematical expression of a ...
Graph clustering aims to identify clusters that feature tighter connections between internal nodes t...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Apart from the role the clustering coefficient plays in the definition of the small-world phenomena,...