The simplest centrality metric is degree centrality and it is quite intuitive on the impact of one node in the
network. The degree centrality of a node (or simpler, its degree) is the total number of its immediate neighbours.
Degree centrality can be normalized when it is divided by its maximum possible number .
The notion of eigenvector centrality relies on the same idea, but in a more subtle way: instead of merely counting
the number of links emanating from a node, the idea is that not all links are of the same importance. Thus, links
coming from more important nodes will offer more centrality in a node than links coming from less important
nodes. The idea is definitely recursive and this centrality measurement is calculated using the eigenvalues of the
adjacency matrix.