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 …

Social influence analysis (SIA) is a vast research field that has attracted research interest in
many areas. In this paper, we present a survey of representative and state-of-the-art work in …

Influence Maximization (IM) is a classical combinatorial optimization problem, which can be
widely used in mobile networks, social computing, and recommendation systems. It aims at …

Bad information propagation in online social networks (OSNs) can cause undesirable
effects. The opposite good information propagating competitively with bad information can …

Abstract The selfish On-Board-Unit (OBU) attacks Vehicular Ad-Hoc Network (VANET) by
various attacks for profit. However, many existing methods are based on the principle of …

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 …

Workers recruitment remains a significant issue in Mobile Crowdsourcing (MCS), where the
aim is to recruit a group of workers that maximizes the expected Quality of Service (QoS) …

Influence maximization (IM) problem, a fundamental algorithmic problem, is the problem of
selecting a set of k users (refer as seed set) from a social network to maximize the expected …

People use online social networks to exchange information, spread ideas, learn about
innovations, etc. Thus, it is important to know how information spreads through social …