Identifying critical nodes via link equations and deep reinforcement learning

P Chen, W Fan - Neurocomputing, 2023 - Elsevier
Identifying an optimal set of nodes that can maximize the spread of influence in a network is
a crucial challenge in network science. It has numerous applications such as epidemic …

Learning to rank influential nodes in complex networks via convolutional neural networks

W Ahmad, B Wang, S Chen - Applied Intelligence, 2024 - Springer
Identifying influential nodes is crucial for enhancing information diffusion in complex
networks. Several approaches have been proposed to find these influential nodes based on …

Influencer Identification on Link Predicted Graphs

LP Schaposnik, R Wu - arXiv preprint arXiv:2402.03522, 2024 - arxiv.org
How could one identify a potential influencer, or how would admissions look like in a
University program for influencers? In the realm of social network analysis, influence …

Identification of spreading influence nodes via multi-level structural attributes based on the graph convolutional network

Y Ou, Q Guo, JL Xing, JG Liu - Expert Systems with Applications, 2022 - Elsevier
The network structural properties at the micro-level, community-level and macro-level have
different contributions to the spreading influence of nodes. The challenge is how to make …

Unveiling Influence in Networks: A Novel Centrality Metric and Comparative Analysis through Graph-Based Models

N Bendahman, D Lotfi - Entropy, 2024 - mdpi.com
Identifying influential actors within social networks is pivotal for optimizing information flow
and mitigating the spread of both rumors and viruses. Several methods have emerged to …

Identifying critical nodes in complex networks via graph convolutional networks

EY Yu, YP Wang, Y Fu, DB Chen, M Xie - Knowledge-Based Systems, 2020 - Elsevier
Critical nodes of complex networks play a crucial role in effective information spreading.
There are many methods have been proposed to identify critical nodes in complex networks …

[PDF][PDF] A Deep Reinforcement Learning Approach for Influence Maximization in Dynamic Non-Progressive Social Networks

Y Hui - 2024 - studenttheses.uu.nl
Influence maximization is pivotal in network analysis, identifying critical individuals for
optimal information spread. This thesis introduces a novel dynamic non-progressive …

Identifying influential nodes in complex networks via Transformer

L Chen, Y Xi, L Dong, M Zhao, C Li, X Liu… - Information Processing & …, 2024 - Elsevier
In the domain of complex networks, the identification of influential nodes plays a crucial role
in ensuring network stability and facilitating efficient information dissemination. Although the …

Identifying critical nodes in complex networks by graph representation learning

E Yu, D Chen, Y Fu, Y Xu - arXiv preprint arXiv:2201.07988, 2022 - arxiv.org
Because of its wide application, critical nodes identification has become an important
research topic at the micro level of network science. Influence maximization is one of the …

Locating influential nodes in complex networks

FD Malliaros, MEG Rossi, M Vazirgiannis - Scientific reports, 2016 - nature.com
Understanding and controlling spreading processes in networks is an important topic with
many diverse applications, including information dissemination, disease propagation and …