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. The data that support the findings of this study are available from the corresponding author upon reasonable request. The code that supports the findings of this study is available from the corresponding author upon reasonable request. Data Availability Code Availability 25/29