Graph neural networks (GNNs) have achieved tremendous success on multiple graph-
based learning tasks by fusing network structure and node features. Modern GNN models …

The identification of spreading influence nodes in social networks, which studies how to
detect important individuals in human society, has attracted increasing attention from …

Social network structure has often been attributed to two network evolution mechanisms—
triadic closure and choice homophily—which are commonly considered independently or …

Influence maximization (IM) problem, a fundamental algorithmic problem, is the problem of
selecting a set of k users (refer as seed set) from a social network to maximize the expected …

The heterogeneous distributions of individual activity and attractiveness can significantly
affect the dynamic processes in time-varying networks. Here we study the impacts of the …

Mixing patterns (MPs) in social trust networks (STNs) are increasingly attracting attention
because they can assist analysts in designing information dissemination tactics and …

Unveiling individuals' preferences for connecting with similar others (choice homophily)
beyond the structural factors determining the pool of opportunities, is a challenging task …

Identifying influential nodes in complex network with community structures attracts lots of
attention recently. In this paper, by combining the community structure identification method …

Identifying the influential nodes of complex networks is now seen as essential for optimizing
the network structure or efficiently disseminating information through networks. Most of the …

The year of 2017 for the 50th anniversary of the Turing Award, which represents the top-
level award in the computer science field, is a milestone. We study the long-term evolution of …