A survey on information diffusion in online social networks: Models and methods
M Li, X Wang, K Gao, S Zhang - Information, 2017 - mdpi.com
By now, personal life has been invaded by online social networks (OSNs) everywhere. They
intend to move more and more offline lives to online social networks. Therefore, online …
intend to move more and more offline lives to online social networks. Therefore, online …
Influence maximization on social graphs: A survey
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 …
network to maximize the expected number of influenced users (called influence spread), is a …
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 …
Real-time influence maximization on dynamic social streams
Influence maximization (IM), which selects a set of $ k $ users (called seeds) to maximize the
influence spread over a social network, is a fundamental problem in a wide range of …
influence spread over a social network, is a fundamental problem in a wide range of …
Reinforcement-learning-based competitive opinion maximization approach in signed social networks
Competitive opinion maximization (COM) in signed social networks targets at selecting a
subset of influential individuals (ie, seed nodes), spreading the desired opinions of the …
subset of influential individuals (ie, seed nodes), spreading the desired opinions of the …
Maximizing positive influence in competitive social networks: A trust-based solution
Online social networks provide convenience for users to propagate ideas, products,
opinions, and many other items that compete with different items for influence spread. How …
opinions, and many other items that compete with different items for influence spread. How …
Competitive and complementary influence maximization in social network: A follower's perspective
The problem of influence maximization is to select a small set of seed users in a social
network to maximize the spread of influence. Recently, this problem has attracted …
network to maximize the spread of influence. Recently, this problem has attracted …
A Memetic algorithm for determining robust and influential seeds against structural perturbances in competitive networks
S Wang, X Tan - Information Sciences, 2023 - Elsevier
The influence maximization problem has attracted increasing attention in previous studies.
Recent years have witnessed an enormous interest in the modeling, performance …
Recent years have witnessed an enormous interest in the modeling, performance …
PIANO: Influence maximization meets deep reinforcement learning
H Li, M Xu, SS Bhowmick, JS Rayhan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Since its introduction in 2003, the influence maximization (IM) problem has drawn significant
research attention in the literature. The aim of IM, which is NP-hard, is to select a set of k …
research attention in the literature. The aim of IM, which is NP-hard, is to select a set of k …
Disco: Influence maximization meets network embedding and deep learning
Since its introduction in 2003, the influence maximization (IM) problem has drawn significant
research attention in the literature. The aim of IM is to select a set of k users who can …
research attention in the literature. The aim of IM is to select a set of k users who can …