All beauty, richness and harmony in the emergent dynamics of a complex system largely
depend on the specific way in which its elementary components interact. The last twenty-five …

Network science has evolved into an indispensable platform for studying complex systems.
But recent research has identified limits of classical networks, where links connect pairs of …

Complex networks have become the main paradigm for modelling the dynamics of
interacting systems. However, networks are intrinsically limited to describing pairwise …

Gathering events, eg, going to gyms and meetings, are ubiquitous and crucial in the
spreading phenomena, which induce higher-order interactions, and thus can be described …

Influence maximization (IM) has shown wide applicability in immense fields over the past
decades. Previous researches on IM mainly focused on the dyadic relationship but lacked …

Complex networks represent the natural backbone to study epidemic processes in
populations of interacting individuals. Such a modeling framework, however, is naturally …

Going beyond networks, to include higher-order interactions of arbitrary sizes, is a major
step to better describe complex systems. In the resulting hypergraph representation, tools to …

Epidemiological models based on traditional networks have made important contributions to
the analysis and control of malware, disease, and rumor propagation. However, higher …

Contagion processes on networks, including disease spreading, information diffusion, or
social behaviors propagation, can be modeled as simple contagion, ie, as a contagion …

Representing social systems as networks, starting from the interactions between individuals,
sheds light on the mechanisms governing their dynamics. However, networks encode only …