Three measures of clumpiness of complex networks are introduced. The measures quantify how most central nodes of a network are clumped together. The assortativity coefficient defined in a previous study measures a similar characteristics but accounts only for the clumpiness of the central nodes that are directly connected to each other. The clumpiness coefficient defined in the present paper also takes into account the cases where central nodes are separated by few links. The definition is based on the node degrees and the distances between pairs of nodes. The clumpiness coefficient together with the assortativity coefficient can define four classes of networks. Numerical calculations demonstrate that the classification scheme successfully ...
<p>The coefficient of assortativity (<i>r</i>) reflects the assortative mixing topology of a network...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, and soc...
Three measures of clumpiness of complex networks are introduced. The measures quantify how most cent...
Author name used in this publication: Xiao-Ke Xu2009-2010 > Academic research: refereed > Publicatio...
We propose a new measure of the communicability of a complex network, which is a broad generalizatio...
Understanding the causes and effects of network structural features is a key task in deciphering com...
AbstractAssortativity quantifies the tendency of nodes being connected to similar nodes in a complex...
Why are some networks degree-degree correlated (assortative), while most of the real-world ones are ...
AbstractWe seek to identify one or more computationally light-weight centrality metrics that have a ...
Complex networks represent an extensive variety of systems in nature and human interactions. Network...
Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to l...
Understanding the causes and effects of network structural features is a key task in deciphering com...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
AbstractMany social, biological or technological systems are recognized as complex networks with ass...
<p>The coefficient of assortativity (<i>r</i>) reflects the assortative mixing topology of a network...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, and soc...
Three measures of clumpiness of complex networks are introduced. The measures quantify how most cent...
Author name used in this publication: Xiao-Ke Xu2009-2010 > Academic research: refereed > Publicatio...
We propose a new measure of the communicability of a complex network, which is a broad generalizatio...
Understanding the causes and effects of network structural features is a key task in deciphering com...
AbstractAssortativity quantifies the tendency of nodes being connected to similar nodes in a complex...
Why are some networks degree-degree correlated (assortative), while most of the real-world ones are ...
AbstractWe seek to identify one or more computationally light-weight centrality metrics that have a ...
Complex networks represent an extensive variety of systems in nature and human interactions. Network...
Assortative mixing in networks is the tendency for nodes with the same attributes, or metadata, to l...
Understanding the causes and effects of network structural features is a key task in deciphering com...
We propose a non-linear relationship between two of the most important measures of centrality in a n...
AbstractMany social, biological or technological systems are recognized as complex networks with ass...
<p>The coefficient of assortativity (<i>r</i>) reflects the assortative mixing topology of a network...
We develop a full theoretical approach to clustering in complex networks. A key concept is introduce...
Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, and soc...