tethne.analyze.graph module

Methods for network analysis.

global_closeness_centrality	Calculates global closeness centrality for all nodes in the network.
node_global_closeness_centrality	Calculates the global closeness centrality of a single node in the network.

tethne.analyze.graph.global_closeness_centrality(g, normalize=True)

Calculates global closeness centrality for all nodes in the network.

See node_global_closeness_centrality() for more information.

Parameters:

g : networkx.Graph

normalize : boolean

If True, normalizes centrality based on the average shortest path length. Default is True.

Returns:

C : dict

Dictionary of results, with node identifiers as keys and gcc as values.

tethne.analyze.graph.node_global_closeness_centrality(g, node, normalize=True)

Calculates the global closeness centrality of a single node in the network.

Closeness centrality is based on the average shortest path length between a focal node and all other nodes in the network. For multi-component graphs, conventional closeness centrality metrics fail because it is not possible to traverse between a given node and all other nodes in the graph. Global closeness centrality is calculated in a way that yields values even for multi-component graphs. For an example of how global closeness centrality can be used to analyze co-authorship networks, see the blog post here.

To calculate the global closeness centrality of a single node, try:

>>> import tethne.analyze as az
>>> ngbc = az.node_global_closeness_centrality(BC, 'LEE 1975 EVOLUTION')
>>> ngbc
0.154245

You can calculate the global closeness centrality of all nodes in the network using global_closeness_centrality() .

>>> GBC = az.global_closeness_centrality(BC)
>>> GBC
{'a': 0.0, 'c': 0.0, 'b': 0.6666666666666666, 'd': 0.0}

For connected graphs, this is equivalent to conventional betweenness centrality. For disconnected graphs, works around infinite path lengths between nodes in different components.

Parameters:

g : networkx.Graph

node : any

Identifier of node of interest in g.

normalize : boolean

If True, normalizes centrality based on the average shortest path length. Default is True.

Returns:

c : float

Global closeness centrality of node.