Social influence and influence diffusion has been widely studied in online social networks.
However, most existing works on influence diffusion focus on static networks. In this paper …

Influence maximization is the problem of finding a small set of most influential nodes in a
social network so that their aggregated influence in the network is maximized. In this paper …

Influence maximization is a fundamental research problem in social networks. Viral
marketing, one of its applications, is to get a small number of users to adopt a product, which …

There is significant current interest in the problem of influence maximization: given a
directed social network with influence weights on edges and a number k, find k seed nodes …

As social network services connect people across the world, influence maximization, ie,
finding the most influential nodes (or individuals) in the network, is being actively researched …

Influence maximization is the problem of selecting top k seed nodes in a social network to
maximize their influence coverage under certain influence diffusion models. In this paper …

Influence maximization, defined as finding a small subset of nodes that maximizes spread of
influence in social networks, is NP-hard under both Linear Threshold (LT) and Independent …

Influence maximization is the problem of finding a set of influential users in a social network
such that the expected spread of influence under a certain propagation model is maximized …

The majority of influence maximization (IM) studies focus on targeting influential seeders to
trigger substantial information spread in social networks. In this paper, we consider a new …

Influence maximization, defined by Kempe, Kleinberg, and Tardos (2003), is the problem of
finding a small set of seed nodes in a social network that maximizes the spread of influence …