Many real-world relations can be represented by signed networks with positive and negative
links, as a result of which signed network analysis has attracted increasing attention from …

For communities of agents which are not necessarily cooperating, distributed processes of
opinion forming are naturally represented by signed graphs, with positive edges …

Hidden Markov modeling is a probabilistic technique for the study of time series. Hidden
Markov theory permits modeling with many of the classical probability distributions. The …

Recommender systems play a crucial role in mitigating the information overload problem in
social media by suggesting relevant information to users. The popularity of pervasively …

Social networks are inevitable part of modern life. A class of social networks is those with
both positive (friendship or trust) and negative (enmity or distrust) links. Ranking nodes in …

Signed directed networks with positive or negative links convey rich information such as like
or dislike, trust or distrust. Existing work of sign prediction mainly focuses on triangles (triadic …

Signed social networks have become increasingly important in recent years because of the
ability to model trust-based relationships in review sites like Slashdot, Epinions, and …

A large portion of today's big data can be represented as networks. However, not all
networks are the same, and in fact, for many that have additional complexities to their …

Many applied problems can be posed as a dynamical system defined on a network with
attractive and repulsive interactions. Examples include synchronization of nonlinear …

We suggest a novel approach to determining the centrality measures for directed signed
networks, based on the notion of social balance. We postulate that along with the existing …