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 …

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 an integral part of the modern lifestyle, and the use of
OSN is highly prevalent today. OSNs have enabled the generation of unprecedented …

Conformity is a type of social influence involving a change in opinion or behavior in order to
fit in with a group. Employing several social networks as the source for our experimental …

As a fundamental problem in social influence propagation analysis, learning influence
parameters has been extensively investigated. Most of the existing methods are proposed to …

Influence maximization (im) is the problem of finding a small subset of nodes (seed nodes)
in a social network that could maximize the spread of influence. Despite the progress …

Trust-based recommender systems improve rating prediction with respect to Collaborative
Filtering by leveraging the additional information provided by a trust network among users to …

It has been observed that individuals' decisions to adopt a product or innovation are often
influenced by the recommendations of their friends and acquaintances. Motivated by this …

Several approaches focus on how to automatically capture the latent features from original
diffusion data and predict the future scale of cascades utilizing a black box framework …

The measurement of influence in social networks has received a lot of attention in the data
mining community. Influence maximization refers to the process of finding influential users …