Understanding graph-based trust evaluation in online social networks: Methodologies and challenges
Online Social Networks (OSNs) are becoming a popular method of meeting people and
keeping in touch with friends. OSNs resort to trust evaluation models and algorithms to …
keeping in touch with friends. OSNs resort to trust evaluation models and algorithms to …
[HTML][HTML] Influence maximization frameworks, performance, challenges and directions on social network: A theoretical study
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 …
network to provide solutions for real-world problems like outbreak detection, viral marketing …
Stop-and-stare: Optimal sampling algorithms for viral marketing in billion-scale networks
Influence Maximization (IM), that seeks a small set of key users who spread the influence
widely into the network, is a core problem in multiple domains. It finds applications in viral …
widely into the network, is a core problem in multiple domains. It finds applications in viral …
A survey on influence maximization in a social network
Given a social network with diffusion probabilities as edge weights and a positive integer k,
which k nodes should be chosen for initial injection of information to maximize the influence …
which k nodes should be chosen for initial injection of information to maximize the influence …
Debunking the myths of influence maximization: An in-depth benchmarking study
Influence maximization (IM) on social networks is one of the most active areas of research in
computer science. While various IM techniques proposed over the last decade have …
computer science. While various IM techniques proposed over the last decade have …
Holistic influence maximization: Combining scalability and efficiency with opinion-aware models
The steady growth of graph data from social networks has resulted in wide-spread research
in finding solutions to the influence maximization problem. In this paper, we propose a …
in finding solutions to the influence maximization problem. In this paper, we propose a …
Dynamic opinion maximization in social networks
Opinion Maximization (OM) aims at determining a small set of influential individuals,
spreading the expected opinions of an object (eg, product or individual) to their neighbors …
spreading the expected opinions of an object (eg, product or individual) to their neighbors …
A new algorithm for positive influence maximization in signed networks
W Ju, L Chen, B Li, W Liu, J Sheng, Y Wang - Information Sciences, 2020 - Elsevier
With the rapid development of online social networks, the problem of influence maximization
(IM) has attracted much attention from researchers and has been applied in many areas …
(IM) has attracted much attention from researchers and has been applied in many areas …
Positive opinion maximization in signed social networks
Opinion maximization is a kind of optimization method, which leverages a subset of
influential nodes in social networks to spread user opinions towards the target product and …
influential nodes in social networks to spread user opinions towards the target product and …
Least cost influence maximization across multiple social networks
Recently, in online social networks (OSNs), the least cost influence (LCI) problem has
become one of the central research topics. It aims at identifying a minimum number of seed …
become one of the central research topics. It aims at identifying a minimum number of seed …