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 …

Online social networks play a pivotal role in the propagation of information and influence as
in the form of word-of-mouth spreading. Influence maximization (IM) is a fundamental …

Influence maximization (IM) is the process of choosing a set of seeds from a social network
so that the most individuals will be influenced by them. Calculating the social effect of a …

A misinformation prevention problem is essential in social networks since misinformation
could greatly mislead people and interfere societal, economical, or even political …

Fueled by the increasing popularity of online social networks, social influence analysis has
attracted a great deal of research attention in the past decade. The diffusion process is often …

Companies aim to promote their products under competitions and try to gain more profit than
other companies. This problem is formulated as a Competitive Influence Maximization (CIM) …

Time plays a critical role in competitive influence maximization. Companies aim to promote
their products before certain events, such as Christmas Eve or music concerts, to gain more …

Influence maximization (IM) is a key problem in social network analysis, which has attracted
attention of many scholars due to the wide range of applications, the variety of IM algorithms …