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.
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>
.