The power of any kind of network approach lies in the ability to simplify a complex system so
that one can better understand its function as a whole. Sometimes it is beneficial, however …

Persistence is an important characteristic of many complex systems in nature, related to how
long the system remains at a certain state before changing to a different one. The study of …

Many networks are dynamic in that their topology changes rapidly—on the same time scale
as the communications of interest between network nodes. Examples are the human contact …

Numerous centrality measures have been developed to quantify the importances of nodes in
time-independent networks, and many of them can be expressed as the leading eigenvector …

Opinion leaders in online social networks are important for various fields such as public
opinion propagation, marketing management, administrative science and even politics …

I briefly survey several fascinating topics in networks and nonlinearity. I highlight a few
methods and ideas, including several of personal interest, that I anticipate to be especially …

Due to the inaccuracy, incompleteness and noise in data from real applications, uncertainty
is a natural feature of real-world networks. In such networks, each edge is associated with a …

Link prediction in social networks has attracted increasing attention in various fields such as
sociology, anthropology, information science, and computer science. Most existing methods …

An algorithm for link prediction in a bipartite network is presented. In the algorithm, we first
map the bipartite network onto a unipartite network called a projected graph. Based on the …

Characterizing the importances (ie, centralities) of nodes in social, biological, and
technological networks is a core topic in both network analysis and data science. We …