Complex networks are ubiquitous: a cell, the human brain, a group of people and the
Internet are all examples of interconnected many-body systems characterized by …

Signal propagation in complex networks drives epidemics, is responsible for information
going viral, promotes trust and facilitates moral behavior in social groups, enables the …

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 …

The brain is characterized by heterogeneous patterns of structural connections supporting
unparalleled feats of cognition and a wide range of behaviours. New non-invasive imaging …

In recent years the research community has accumulated overwhelming evidence for the
emergence of complex and heterogeneous connectivity patterns in a wide range of …

The propagations of diseases, behaviors and information in real systems are rarely
independent of each other, but they are coevolving with strong interactions. To uncover the …

Since the publication of “Complex Contagions and the Weakness of Long Ties” in 2007,
complex contagions have been studied across an enormous variety of social domains. In …

We investigate the impact of community structure on information diffusion with the linear
threshold model. Our results demonstrate that modular structure may have counterintuitive …

A wide class of binary-state dynamics on networks—including, for example, the voter model,
the Bass diffusion model, and threshold models—can be described in terms of transition …

Binary-state dynamics (such as the susceptible-infected-susceptible (SIS) model of disease
spread, or Glauber spin dynamics) on random networks are accurately approximated using …