By now, personal life has been invaded by online social networks (OSNs) everywhere. They
intend to move more and more offline lives to online social networks. Therefore, online …

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 …

Influence maximization (IM) is formulated as selecting a set of initial users from a social
network to maximize the expected number of influenced users. Researchers have made …

Influence Maximization (IM), which selects a set of k users (called seed set) from a social
network to maximize the expected number of influenced users (called influence spread), is a …

Influence maximization (IM) has shown wide applicability in immense fields over the past
decades. Previous researches on IM mainly focused on the dyadic relationship but lacked …

Influence maximization is a classic and extensively studied problem with important
applications in viral marketing. Existing algorithms for influence maximization, however …

In this paper, we address the important issue of uncertainty in the edge influence probability
estimates for the well studied influence maximization problem---the task of finding k seed …

With the increasing development of social networks, they have turned into important
research platforms. Influence maximization is one of the most important research issues in …

We study the online influence maximization problem in social networks under the
independent cascade model. Specifically, we aim to learn the set of" best influencers" in a …

Given a social network G with n nodes and m edges, a positive integer k, and a cascade
model C, the influence maximization (IM) problem asks for k nodes in G such that the …