Article,
Popularity versus similarity in growing networks
Nature, (Sep 12, 2012)
DOI: 10.1038/nature11459
Abstract
Preferential attachment is a powerful mechanism explaining the emergence of
scaling in growing networks. If new connections are established preferentially
to more popular nodes in a network, then the network is scale-free. Here we
show that not only popularity but also similarity is a strong force shaping the
network structure and dynamics. We develop a framework where new connections,
instead of preferring popular nodes, optimize certain trade-offs between
popularity and similarity. The framework admits a geometric interpretation, in
which preferential attachment emerges from local optimization processes. As
opposed to preferential attachment, the optimization framework accurately
describes large-scale evolution of technological (Internet), social (web of
trust), and biological (E.coli metabolic) networks, predicting the probability
of new links in them with a remarkable precision. The developed framework can
thus be used for predicting new links in evolving networks, and provides a
different perspective on preferential attachment as an emergent phenomenon.
