Barabasi AL, Jeong H, Neda Z, Ravasz E, Schubert A, Vicsek T. "Evolution of the social network of scientific collaborations" PHYSICA A 311 (3-4): 590-614 AUG 15 2002

[Eugene Garfield]

A.L. Barabasi: Albert.L.Barabasi.1 at nd.edu


Title Evolution of the social network of scientific collaborations
Author Barabasi AL, Jeong H, Neda Z, Ravasz E, Schubert A, Vicsek T
Journal PHYSICA A 311 (3-4): 590-614 AUG 15 2002

 Document type: Article    Language: English    Cited References: 42
Times Cited: 0


Abstract:
The co-authorship network of scientists represents a prototype of complex
evolving networks. In addition, it offers one of the most extensive database
to date on social networks. By mapping the electronic database containing
all relevant journals in mathematics and neuro-science for an 8-year period
(1991-98), we infer the dynamic and the structural mechanisms that govern
the evolution and topology of this complex system. Three complementary
approaches allow us to obtain a detailed characterization. First, empirical
measurements allow us to uncover the topological measures that characterize
the network at a given moment, as well as the time evolution of these
quantities. The results indicate that the network is scale-free, and that
the network evolution is governed by preferential attachment, affecting both
internal and external links. However, in contrast with most model
predictions the average degree increases in time, and the node separation
decreases. Second,
we propose a simple model that captures the network's time evolution. In
some limits the model can be solved analytically, predicting a two-regime
scaling in agreement with the measurements. Third, numerical simulations are
used to uncover the behavior of quantities that could not be predicted
analytically. The combined numerical and analytical results underline the
important role internal links play in determining the observed scaling
behavior and network topology. The results and
methodologies developed in the context of the co-authorship network could be
useful for a systematic study of other complex evolving networks as well,
such as the world wide web, Internet, or other social networks. (C) 2002
Published by Elsevier Science B.V.

Author Keywords:
random networks, scaling, small-word systems, scale-free networks

KeyWords Plus:
WORLD-WIDE-WEB, GROWING RANDOM NETWORKS, TOPOLOGY, INTERNET, DISTRIBUTIONS,
ORGANIZATION, DYNAMICS,
GROWTH

Addresses:
Barabasi AL, Univ Notre Dame, Dept Phys, Notre Dame, IN 46556 USA
Univ Notre Dame, Dept Phys, Notre Dame, IN 46556 USA
Coll Budepest, Inst Adv Study, Budapest, Hungary
Univ Babes Bolyai, Dept Theoret Phys, R-3400 Cluj Napoca, Romania
Lib Hungarian Acad Sci, Bibliomet Serv, Budapest, Hungary
Lorand Eotvos Univ, Dept Biol Phys, Budapest, Hungary

Publisher:
ELSEVIER SCIENCE BV, AMSTERDAM

IDS Number:
581BK

ISSN:
0378-4371

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