The Salton index is $$ \mathbf S_{\text{Salton}}[u,v] = \frac{ 2\lvert \mathcal N (u) \cap \mathcal …

The Sorensen index is $$ \mathbf S_{\text{Sorensen}}[u,v] = \frac{ 2\lvert \mathcal N (u) \cap …

Betweenness centrality of a node $v$ is measurement of how likely the shortest path between two …

Given a graph with adjacency matrix $\mathbf A$, the eigenvector centrality is $$ \mathbf e_u = …

A graph $\mathcal G$ can be represented with an adjacency matrix $\mathbf A$. There are some nice …

Local Clustering Coefficient $$ c_u = \frac{ \lvert (v_1,v_2)\in \mathcal E: v_1, v_2 \in \mathcal …

Cut For a subset of nodes $\mathcal A\subset \mathcal V$, the rest of nodes can be denoted as $\bar …

Laplacian is a useful representation of graphs. The unnormalized Laplacian is $$ \mathbf L = \mathbf …

Heterophily is the tendency to differ from others. Heterophily on a graph is the tendency to connect …

Homophily is the principle that a contact between similar people occurs at ahigher rate than among …

Node degree of a node $u$ $$ d_u = \sum_{v\in \mathcal V} A[u,v], $$ where $A$ is the adjacency …

Structural Equivalence means that nodes with similar neighborhood structures will share similar …

The Weisfeiler-Lehman kernel is an iterative integration of neighborhood information. We initialize …

Introduce geometry into the manifold of complex networks