Literature [13] makes a thorough investigation of both microscale and macroscale metrics including node degree, lobby index, link duration, network diameter, closeness centrality, betweenness centrality, number of communities, clustering coefficients, and so on.
Common descriptive statistics are even more elusive: only 12% of the studies report all standard descriptive statistics for each network (e.g., average and standard deviation for degree centrality, density, average path length, and number of actors and links) and 24% of articles report standardized values, required to directly compare different networks.
We inspected the distribution of the local connectivity, centrality, number of interacting pathogens, and number of pathogen groups for the host proteins in the interaction grouping.
In Fig. 25, we show the Pearson's correlation coefficient between network metrics, namely the degree (k), clustering coefficient (text{ cc }), betweenness (B) and closeness (C) centralities, and the number of papers (p) an author had published.
Fig. 25 The Pearson's correlation coefficient between network metrics (degree (k), clustering coefficient (cc), betweenness (B) and closeness (C) centralities) and the number of papers (p) an author had published.
This allows us to search for a threshold that gives a compromise between high values of centrality and a small number of variables; in so doing, we can identify a significant sub-group of variables with the highest centrality in the network.
Table 2 Social network analysis metrics that allow the identification of key players in wildlife trafficking networks Metric Description Degree centrality The number of links directly connected to that player Betweenness centrality v i is defined as follows.
Those commonly used are the degree centrality (the number of direct neighbors of a node), the betweenness centrality (an index quantifying how frequently a node appears on all shortest paths between all node pairs) and the closeness centrality (an index measuring how close a node is to all others in the same network).
It is coherent that the measure of degree centrality (the number of nodes that connect to a given node) contains more discriminative information in these areas, since the motor network fundamentally comprises the output of the central nervous system.
First, we include the top five countries as determined by degree centrality (ie, number of discussion threads they are present in), which are the same five we had visually found in the country network's core cluster.
