cdlib.algorithms.head_tail¶

head_tail(g_original: object, head_tail_ratio: float = 0.4) → cdlib.classes.node_clustering.NodeClustering¶

Identifying homogeneous communities in complex networks by applying head/tail breaks on edge betweenness given its heavy-tailed distribution.

Note: this implementation is suited for small-medium sized graphs, and it may take couple of minutes or longer for a bigger graph.

Supported Graph Types

Undirected	Directed	Weighted
Yes	No	No

Parameters:	g_original – a networkx/igraph object head_tail_ratio – head/tail division rule. Float in [0,1], dafault 0.4.
Returns:	NodeClustering object
Example:

>>> from cdlib import algorithms
>>> import networkx as nx
>>> G = nx.head_tail()
>>> coms = algorithms.head_tail(G, head_tail_ratio=0.8)

References:

Jiang B. and Ding M. (2015), Defining least community as a homogeneous group in complex networks, Physica A, 428, 154-160.

Note