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March 3, 2026
PPCN: Identifying influential nodes based on propagation probability model considering neighbors in complex networks
BL
Bo Liu
JW
Juncan Wei
KC
Kaile Chen
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Puntos clave
Influential nodes were identified based on a propagation probability model, enhancing understanding of network dynamics.
Key results demonstrate that considering neighboring influences significantly alters node importance rankings.
Employing graph theory techniques, this approach offers a novel perspective on analyzing complex networks.
These findings suggest potential applications in optimizing communication and control within various networked systems.
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Cite This Study
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Liu et al. (Thu,) studied this question.
synapsesocial.com/papers/69a7683cbadf0bb9e87e415e
https://doi.org/https://doi.org/10.1016/j.jocs.2026.102792
PPCN: Identifying influential nodes based on propagation probability model considering neighbors in complex networks | Synapse