The growing popularity of social networks is providing a promising opportunity for different
practical applications. The influence analysis is an essential technique supporting the …

The influence maximization problem has gained increasing attention in recent years.
Previous research focuses on the development of algorithms to analyze static social …

Given a social network with diffusion probabilities as edge weights and a positive integer k,
which k nodes should be chosen for initial injection of information to maximize the influence …

Influence maximization in social networks aims to find a small group of individuals, which
have maximal influence cascades. In this study, an optimization model based on a local …

In complex networks, the nodes with most spreading ability are called influential nodes. In
many applications such as viral marketing, identification of most influential nodes and …

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 …

Influence maximization (IM) is the problem of finding a small subset of nodes in a social
network so that the number of nodes influenced by this subset can be maximized. Influence …

Identifying influential spreaders in complex networks is a fundamental network project. It has
drawn great attention in recent years because of its great theoretical significance and …

Identifying influential spreaders in a complex network has practical and theoretical
significance. In applications such as disease spreading, virus infection in computer …

Influence maximization is to extract a small set of nodes from a social network which
influences the propagation maximally under a cascade model. In this paper, we propose a …