New trends in influence maximization models
The growing popularity of social networks is providing a promising opportunity for different
practical applications. The influence analysis is an essential technique supporting the …
practical applications. The influence analysis is an essential technique supporting the …
A survey on influence maximization models
M Jaouadi, LB Romdhane - Expert Systems with Applications, 2024 - Elsevier
Influence maximization is an important research area in social network analysis where
researchers are concerned with detecting influential nodes. The detection of influential …
researchers are concerned with detecting influential nodes. The detection of influential …
A new consensus model based on trust interactive weights for intuitionistic group decision making in social networks
X Ma, Z Gong, G Wei… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A promising feature for group decision making (GDM) lies in the study of the interaction
between individuals. In conventional GDM research, experts are independent. This is …
between individuals. In conventional GDM research, experts are independent. This is …
Influence maximization in complex networks by using evolutionary deep reinforcement learning
Influence maximization (IM) in complex networks tries to activate a small subset of seed
nodes that could maximize the propagation of influence. The studies on IM have attracted …
nodes that could maximize the propagation of influence. The studies on IM have attracted …
Lss: a locality-based structure system to evaluate the spreader's importance in social complex networks
Assessing the importance of spreaders in networks is crucial for investigating the survival
and robustness of networks. There are numerous potential applications, such as preventing …
and robustness of networks. There are numerous potential applications, such as preventing …
A new community-based algorithm based on a “peak-slope-valley” structure for influence maximization on social networks
Influence Maximization (IM) is a key algorithmic problem that has been extensively studied
in social influence analysis, but most of existing researches either make sacrifices in solution …
in social influence analysis, but most of existing researches either make sacrifices in solution …
Influence maximization problem by leveraging the local traveling and node labeling method for discovering most influential nodes in social networks
The influence maximization problem has gained particular importance in viral marketing for
large-scale spreading in social networks. Developing a fast and appropriate algorithm to …
large-scale spreading in social networks. Developing a fast and appropriate algorithm to …
A computationally efficient evolutionary algorithm for multiobjective network robustness optimization
The robustness of complex networks is of great significance. Great achievements have been
made in robustness optimization based on single measures, however, such networks may …
made in robustness optimization based on single measures, however, such networks may …
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 …
Detecting k-Vertex Cuts in Sparse Networks via a Fast Local Search Approach
The-vertex cut (-VC) problem belongs to the family of the critical node detection problems,
which aims to find a minimum subset of vertices whose removal decomposes a graph into at …
which aims to find a minimum subset of vertices whose removal decomposes a graph into at …