Abstract
In the field of social networks rumor control, finding the important nodes with the greatest propagating influence is of great practical importance to effectively control the propagation of rumors. In order to solve the problem that the network coupling information and information transfer mechanism in the existing node importance metric affects the accuracy of the metric, we propose a measure of node importance based on multiple feature fusion (MFF). The method uses an improved Dempster–Shafer evidence theory to fuse the centrality, transmissibility, and prestige measurement of nodes and rank the importance of nodes based on the fusion results. The proposed method was first evaluated against similar methods on six real networks in terms of robustness and vulnerability, as well as in terms of SIR propagation characteristics. Then, we simulated the changes in the number of users who believed the rumor after the rumor was propagated in three cases: before the control, after suppress rumors by random nodes, and after suppress rumors by important nodes. The experimental results show that the proposed method is more accurate for node importance measurement and more effective in rumor control.
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The data used to support the findings of this study are available from the corresponding author upon request.
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Funding
The work was sponsored by National Natural Science Foundation of China (No. 61972133), the Opening Foundation of Yunnan Key Laboratory of Smart City in Cyberspace Security (No. 202105AG070010).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Y-CW, M-JH and G-MY. Conceptualization and visualization were performed by Z-QW and S-YG. The first draft of the manuscript was written by Y-CW and all authors commented on previous versions of the manuscript. In particular, JW and JY contributed the most to writing—review and supervision. All authors read and approved the final manuscript.
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Wang, YC., Wang, J., Huang, MJ. et al. A multiple features fusion-based social network node importance measure for rumor control. Soft Comput 28, 2501–2516 (2024). https://doi.org/10.1007/s00500-023-08510-4
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DOI: https://doi.org/10.1007/s00500-023-08510-4