From Complex Networks to Human Travel Patterns Albert-László Barabási Albert-László Barabási Center for Complex Networks Research Center for Complex Networks Research Northeastern University Northeastern University Department of Medicine and CCSB Department of Medicine and CCSB Harvard Medical School Harvard Medical School www.BarabasiLab.com
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From Complex Networks to Human Travel Patterns Albert-László Barabási Center for Complex Networks Research Northeastern University Department of Medicine.
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From Complex Networks
to
Human Travel Patterns
Albert-László BarabásiAlbert-László BarabásiCenter for Complex Networks ResearchCenter for Complex Networks Research
Northeastern UniversityNortheastern University
Department of Medicine and CCSBDepartment of Medicine and CCSB
Harvard Medical School Harvard Medical School
www.BarabasiLab.com
Erdös-Rényi model (1960)
- Democratic
- Random
Pál ErdösPál Erdös (1913-1996)
Connect with probability p
p=1/6 N=10
k ~ 1.5 Poisson distribution
World Wide Web
Over 10 billion documents
ROBOT: collects all URL’s found in a document and follows them recursively
Nodes: WWW documents Links: URL links
R. Albert, H. Jeong, A-L Barabási, Nature, 401 130 (1999).
Exp
ected
P(k) ~ k-
Fou
nd
Sca
le-f
ree
Netw
ork
Exp
on
en
tial
Netw
ork
INTERNET BACKBONE
(Faloutsos, Faloutsos and Faloutsos, 1999)
Nodes: computers, routers Links: physical lines
Origin of SF networks: Growth and preferential attachment
Barabási & Albert, Science 286, 509 (1999)
jj
ii k
kk
)(
P(k) ~k-3
(1) Networks continuously expand by the addition of new nodesWWW : addition of new documents
GROWTH: add a new node with m links
PREFERENTIAL ATTACHMENT: the probability that a node
connects to a node with k links is proportional to k.
(2) New nodes prefer to link to highly connected nodes.WWW : linking to well known sites
Metabolic Network Protein Interactions
Jeong, Tombor, Albert, Oltvai, & Barabási, Nature (2000); Jeong, Mason, Barabási &. Oltvai, Nature (2001); Wagner & Fell, Proc. R. Soc. B (2001)
RobustnessComplex systems maintain their basic functions even under errors
and failures (cell mutations; Internet router breakdowns)
node failure
fc
0 1Fraction of removed nodes, f
1
S
Robustness of scale-free networks
1
S
0 1f
fc
Attacks
3 : fc=1
(R. Cohen et al PRL, 2000)
Failures
Albert, Jeong, Barabási, Nature 406 378 (2000)
Don’t forget the
movie again!
Don’t forget the
movie again!
Human MotionHuman Motion
Brockmann, Hufnagel, Geisel Nature (2006)
Dollar Bill MotionDollar Bill Motion
Brockmann, Hufnagel, Geisel Nature (2006)
A real human trajectory
Mobile Phone Users
0 km 300 km100 km 200 km
0 k
m10
0 k
m20
0 k
mMobile Phone Users
Two possible explanations
1. Each users follows a Lévy flight
2. The difference between individuals follows a power law