number of edges connecting to a given node, given by k$_{i}$ =$_{GLYPH<229>}$$_{j}$ A$_{i j}$ where A is the adjacency matrix. The clustering coefficient can be defined as the fraction of possible edges between a node’s neighbors, given by C$_{i}$ = 2 L$_{i}$ k$_{i}$ ( k$_{i}$ − 1 ) where L$_{i}$ is the number of edges between any two neighbors of node i . The node betweenness centrality is defined as the fraction of shortest paths in the graph that pass through node v , given by C$_{B}$ ( v ) =$_{GLYPH<229>}$$_{s}$$_{̸}$$_{=}$$_{v}$$_{̸}$$_{=}$$_{t}$ s $_{st}$(v ) s st where $_{s$_{st}$}$( v ) is the number of shortest paths from node s to node t that pass through node v , and$_{s}$$_{st}$ is the total number of shortest paths in the graph from node s to node t . The edge betweenness centrality is defined as the fraction of shortest paths passing through an edge e , given by C$_{B}$ ( e ) =$_{GLYPH<229>}$$_{s}$$_{̸}$$_{=}$$_{e}$$_{̸}$$_{=}$$_{t}$ s $_{st}$(e ) s st , where now e refers to an edge rather than a node. 

## Data Availability 

The data that support the findings of this study are available from the corresponding author upon reasonable request. 

## Code Availability 

The code that supports the findings of this study is available from the corresponding author upon reasonable request. 

