Network analysis

method of cluster analysis which seeks to build a hierarchy of clusters

number defined from a node-link network quantifying how likely it is that two neighbors of a randomly chosen node will be adjacent

In graph theory and network analysis, indicators of centrality assign numbers or rankings to nodes within a graph corresponding to their network position. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, super-spreaders of disease, and brain networks. Centrality concepts were first developed in social network analysis, and many of the terms used to measure centrality reflect their sociological origin. Over time, the concept has expanded substantially, leading to the development of hundreds of distin

Community detection algorithm

network analysis technique