The influence maximization (IM) problem identifies the subset of influential users in the
network to provide solutions for real-world problems like outbreak detection, viral marketing …

Online Social Networks (OSNs) are becoming a popular method of meeting people and
kee** in touch with friends. OSNs resort to trust evaluation models and algorithms to …

Competitive opinion maximization (COM) aims to determine some individuals (ie, seed
nodes) from social networks, propagating the desired opinions toward a target entity to their …

Influence Maximization (IM), that seeks a small set of key users who spread the influence
widely into the network, is a core problem in multiple domains. It finds applications in viral …

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 (IM) on social networks is one of the most active areas of research in
computer science. While various IM techniques proposed over the last decade have …

Opinion Maximization (OM) aims at determining a small set of influential individuals,
spreading the expected opinions of an object (eg, product or individual) to their neighbors …

The steady growth of graph data from social networks has resulted in wide-spread research
in finding solutions to the influence maximization problem. In this paper, we propose a …

With the rapid development of online social networks, the problem of influence maximization
(IM) has attracted much attention from researchers and has been applied in many areas …

Recently, in online social networks (OSNs), the least cost influence (LCI) problem has
become one of the central research topics. It aims at identifying a minimum number of seed …