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), 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 …

Quantum social network analysis (QSNA) is a recent advancement in the interdisciplinary
field of quantum computing and social network analysis. This manuscript comprehensively …

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 …

Accurately simulating human opinion dynamics is crucial for understanding a variety of
societal phenomena, including polarization and the spread of misinformation. However, the …

Community partition is an important problem in many areas, such as biology networks and
social networks. The objective of this problem is to analyze the relationships among data via …

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 …

Crowd psychology plays an important role in determining the kind of activities that a person
performs. In reality, in a social network, crowd influence has been observed and it cannot be …

Worker recruitment is a crucial research problem in Mobile Crowd Sensing (MCS). While
previous studies rely on a specified platform with a pre-assumed large user pool, this paper …

In this paper, we study the Multi-Round Influence Maximization (MRIM) problem, where
influence propagates in multiple rounds independently from possibly different seed sets, and …