ba - Grow a Barabasi-Albert scale-free random graph
ba N m n0
ba grows an undirected random scale-free graph with N nodes using
the linear preferential attachment model proposed by Barabasi and
Albert. The initial network is a ring of n0 nodes, and each new node
creates m new edges. The resulting graph will have a scale-free
degree distribution, whose exponent converges to gamma=3.0 for large
N.
Number of nodes of the final graph.
Number of edges created by each new node.
Number of nodes in the initial (seed) graph.
ba prints on STDOUT the edge list of the final graph.
The following command:
$ ba 10000 3 5 > ba_10000_3_5.txt
creates a Barabasi-Albert scale-free graph with N=10000 nodes, where
each new node creates m=3 new edges and the initial seed network is
a ring of n0=5 nodes. The edge list of the graph is saved in the
file ba_10000_3_5.txt (thanks to the redirection operator >).
bb_fitness(1), dms(1), bbv(1)
A.-L. Barabasi, R. Albert, "Emergence of scaling in random networks", Science 286, 509-512 (1999).
V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles, Methods and Applications", Chapter 6, Cambridge University Press (2017)
V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles, Methods and Applications", Appendix 13, Cambridge University Press (2017)
(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 <v.nicosia@qmul.ac.uk>.