klusterointikerrointa

Klusterointikerroin, often translated as clustering coefficient or sometimes as aggregation coefficient, is a measure used in graph theory and network analysis to quantify the degree to which nodes in a graph tend to cluster together. It describes how closely connected a node's neighbors are to each other. In simpler terms, it answers the question of how likely it is that two neighbors of a particular node are also neighbors of each other.

There are two main types of clustering coefficients: the local clustering coefficient and the global clustering coefficient. The local clustering coefficient for a specific node measures the density of connections among its immediate neighbors. If a node has many neighbors, and these neighbors are also connected to each other, the local clustering coefficient for that node will be high. Conversely, if the neighbors are sparsely connected, the coefficient will be low.

The global clustering coefficient, on the other hand, provides an overall measure of clustering for the entire network. It can be calculated in a few ways, most commonly as the average of all local clustering coefficients, or by considering the number of triangles (three nodes that are all connected to each other) relative to the total number of possible triangles in the network. A high global clustering coefficient indicates that the network as a whole exhibits a high degree of clustering, meaning that friends of friends are likely to be friends. This metric is useful in understanding the structure and dynamics of various networks, from social networks to biological systems and the internet.