In the last two decades, network science has blossomed and influenced various fields, such
as statistical physics, computer science, biology and sociology, from the perspective of the …

In the past 15 years, statistical physics has been successful as a framework for modelling
complex networks. On the theoretical side, this approach has unveiled a variety of physical …

We bring rigor to the vibrant activity of detecting power laws in empirical degree distributions
in real-world networks. We first provide a rigorous definition of power-law distributions …

Complex systems are very often organized under the form of networks where nodes and
edges are embedded in space. Transportation and mobility networks, Internet, mobile phone …

The observed architecture of ecological and socio-economic networks differssignificantly
from that of random networks. From a network science standpoint, non-random structural …

Professor Barabási's talk described how the tools of network science can help understand
the Web's structure, development and weaknesses. The Web is an information network, in …

We develop a geometric framework to study the structure and function of complex networks.
We assume that hyperbolic geometry underlies these networks, and we show that with this …

Network modeling plays a critical role in identifying statistical regularities and structural
principles common to many systems. The large majority of recent modeling approaches are …

The availability of large data sets has allowed researchers to uncover complex properties
such as large-scale fluctuations and heterogeneities in many networks, leading to the …

This chapter describes the basic variants of the stochastic blockmodel (SBM), and a
consistent Bayesian formulation that allows readers to infer them from data. The focus is on …