Modelling diffusion processes on time-varying networks
Networks, virtually in any domain, are dynamical entities. Think
for example about social networks. New nodes join the system, others
leave it, and links describing their interactions are constantly
changing. However, due to absence of time-resolved data and
mathematical challenges, the large majority of research in the field
neglects these features in favor of static representations. While such
approximation is useful and appropriate in some systems and processes,
it fails in many others. Indeed, in the case of sexual transmitted
diseases, ideas, and meme spreading, the co-occurrence, duration and
order of contacts are crucial ingredients.
During my talk, I will present a novel mathematical framework for the modeling of highly time-varying networks and processes evolving on their fabric. In particular, I will focus on epidemic spreading, random walks, and controlling strategies on temporal networks.