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  2. Closeness centrality - Wikipedia

    en.wikipedia.org/wiki/Closeness_centrality

    In a connected graph, closeness centrality (or closeness) of a node is a measure of centrality in a network, calculated as the reciprocal of the sum of the length of the shortest paths between the node and all other nodes in the graph. Thus, the more central a node is, the closer it is to all other nodes. The number next to each node is the ...

  3. Centrality - Wikipedia

    en.wikipedia.org/wiki/Centrality

    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.

  4. Social network analysis - Wikipedia

    en.wikipedia.org/wiki/Social_network_analysis

    Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. [1] It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them.

  5. Betweenness centrality - Wikipedia

    en.wikipedia.org/wiki/Betweenness_centrality

    Betweenness centrality. An directed graph colored based on the betweenness centrality of each vertex from least (red) to greatest (blue). In graph theory, betweenness centrality is a measure of centrality in a graph based on shortest paths. For every pair of vertices in a connected graph, there exists at least one shortest path between the ...

  6. Hierarchical closeness - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_closeness

    Hierarchical closeness (HC) is a structural centrality measure used in network theory or graph theory. It is extended from closeness centrality to rank how centrally located a node is in a directed network. While the original closeness centrality of a directed network considers the most important node to be that with the least total distance ...

  7. Eigenvector centrality - Wikipedia

    en.wikipedia.org/wiki/Eigenvector_centrality

    In graph theory, eigenvector centrality (also called eigencentrality or prestige score [1]) is a measure of the influence of a node in a connected network.Relative scores are assigned to all nodes in the network based on the concept that connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes.

  8. Katz centrality - Wikipedia

    en.wikipedia.org/wiki/Katz_centrality

    e. In graph theory, the Katz centrality or alpha centrality of a node is a measure of centrality in a network. It was introduced by Leo Katz in 1953 and is used to measure the relative degree of influence of an actor (or node) within a social network. [1] Unlike typical centrality measures which consider only the shortest path (the geodesic ...

  9. Krackhardt kite graph - Wikipedia

    en.wikipedia.org/wiki/Krackhardt_Kite_Graph

    Krackhardt kite graph. In graph theory, the Krackhardt kite graph is a simple graph with ten nodes. The graph is named after David Krackhardt, a researcher of social network theory. [1][2] Krackhardt introduced the graph in 1990 to distinguish different concepts of centrality. It has the property that the vertex with maximum degree (labeled 3 ...