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.
>>> from cdlib import algorithms >>> import networkx as nx >>> G = nx.karate_club_graph() >>> coms = algorithms.head_tail(G, head_tail_ratio=0.8)
Jiang B. and Ding M. (2015), Defining least community as a homogeneous group in complex networks, Physica A, 428, 154-160.
Reference implementation: https://github.com/dingmartin/HeadTailCommunityDetection