Eigenvector centrality
= Eigenvector centrality
{title2=$Av=\lambda_{\max}v$}
<Eigenvector centrality> assigns nonnegative vertex scores proportional to the sum of neighbouring scores: $v_i=\lambda_{\max}^{-1}\sum_jA_{ij}v_j$. It uses a nonnegative <eigenvector> of the <adjacency matrix> for its largest positive <eigenvalue>. State the normalization, such as <Euclidean norm> one. For a three-leaf <star graph>, hub and leaf scores have ratio $\sqrt3$.