Year: 2026
Type: article
Abstract: Immunization strategies primarily aim to block the spreading process of viruses or information and to reduce the negative effects of these processes at a low cost. Previous immunization methods heavily rely on global network information to improve accuracy. However, in many cases, obtaining the global structure information of a network is impossible. Therefore, we propose a novel algorithm that relies on the local structural information of nodes and directly finds the bridge-hub nodes through the self-avoiding random walk algorithm. Compared with the acquaintance immunization method and the existing well-known related algorithms, our proposed algorithm has higher accuracy and stability and is less affected by infection probability. Furthermore, extensive experiments conducted with SIR epidemic model on real-world networks demonstrate that our algorithm can be widely used in the prevention and control of diseases and information in real networks with community structures.
Authors: Dayong Zhang, Xuchen Meng, Jiaye Sheng
Institution: Harbin Institute of Technology
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,190
Awards: G3360951524, G7788505109
OpenAlex ID: W7123356903