What is degree assortativity?

Degree assortativity is the tendency for nodes of high degree (resp. low degree) in a graph to be connected to high degree nodes (resp. to low degree ones). It is usually quantified by the Pearson correlation coefficient of the degree–degree correlation.

How do you interpret assortativity coefficient?

A large positive value means that connected nodes very much tend share similar properties; a large negative value means that connected nodes tend to possess very different properties; and a value close to 0 means no strong association of the property values between connected nodes (where strength is gauged in distance …

Why is assortativity useful?

Application. The properties of assortativity are useful in the field of epidemiology, since they can help understand the spread of disease or cures. For instance, the removal of a portion of a network’s vertices may correspond to curing, vaccinating, or quarantining individuals or cells.

What is degree degree correlation?

Degree-degree correlation indicates the relationship between the node degrees, and it is often defined as the Pearson correlation coefficient of degrees between a connected node pair [4] (i.e., assortative coefficient ra).

What is assortativity in social networks?

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.

What is degree of correlation?

Degree of correlation refers to the Coefficient of Correlation. There can be degrees of positive and negative correlation. Perfect Positive: When the proportional change in two variables is in the same direction, the correlation is perfectly positive. The coefficient of correlation is positive (+1) in this case.