Assortativity
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Assortativity
Assortativity, or assortative mixing is a preference for a network's nodes to attach to others that are similar in some way. Though the specific measure of similarity may vary, network theorists often examine assortativity in terms of a node's degree. The addition of this characteristic to network models more closely approximates the behaviors of many real world networks. Correlations between nodes of similar degree are often found in the mixing patterns of many observable networks. For instance, in social networks, nodes tend to be connected with other nodes with similar degree values. This tendency is referred to as assortative mixing, or ''assortativity''. On the other hand, technological and biological networks typically show disassortative mixing, or ''disassortativity'', as high degree nodes tend to attach to low degree nodes. Measurement Assortativity is often operationalized as a correlation between two nodes. However, there are several ways to capture such a correl ...
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Rich-club Coefficient
The rich-club coefficient is a metric on graphs and networks, designed to measure the extent to which well-connected nodes also connect to each other. Networks which have a relatively high rich-club coefficient are said to demonstrate the rich-club effect and will have many connections between nodes of high degree. The rich-club coefficient was first introduced in 2004 in a paper studying Internet topology.Mattia Gasparini, Javier Luis Canovas Izquierdo, Robert Clariso, Marco Brambilla, Jordi Cabot''Analyzing Rich-Club Behavior in Open Source Projects'' OpenSym 2019 proceedings The "Rich-club" effect has been measured and noted on scientific collaboration networks and air transportation networks. It has been shown to be significantly lacking on protein interaction networks. Definition Non-normalized form The rich-club coefficient was first introduced as an unscaled metric parametrized by node degree ranks. More recently, this has been updated to be parameterized in terms o ...
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