Recent decades have seen a rise in the use of physics methods to study different societal
phenomena. This development has been due to physicists venturing outside of their …

The modern science of networks has made significant advancement in the modeling of
complex real-world systems. One of the most important features in these networks is the …

Abstract Information cascades are important dynamical processes in complex networks. An
information cascade can describe the spreading dynamics of rumour, disease, memes, or …

Link prediction is a technique to forecast future new or missing relationships between nodes
based on the current network information. However, the link prediction in monoplex …

Link prediction is a paradigmatic problem in network science, which aims at estimating the
existence likelihoods of nonobserved links, based on known topology. After a brief …

Networks of species interactions underpin numerous ecosystem processes, but
comprehensively sampling these interactions is difficult. Interactions intrinsically vary across …

Complex networks are representations of real-world systems that can be better modeled as
multiplex networks, where the same nodes develop multi-type connections. One of the …

Influence Maximization is an important problem in social networks, and its main goal is to
select some most influential initial nodes (ie, seed nodes) to obtain the maximal influence …

Some networked systems can be better modeled by multilayer structure where the individual
nodes develop relationships in multiple layers. Multilayer networks with similar nodes across …

Link prediction, a critical pursuit in complex networks research, revolves around the
predictive understanding of connections between nodes. Our novel approach introduces a …