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ARTICLE
Efficient Rumor Control via Disseminating Truthful Information by Influential Nodes
1 Library, Zhengzhou University of Aeronautics, Zhengzhou, 450046, China
2 School of Mathematics, Physics and Computing, University of Southern Queensland, Toowoomba, 4350, Australia
3 Zhengzhou University of Aeronautics, Zhengzhou, 450046, China
4 School of Computer Science, Zhengzhou University of Aeronautics, Zhengzhou, 450046, China
* Corresponding Authors: Lingling Li. Email: ; Xuezhuan Zhao. Email:
Computers, Materials & Continua 2025, 85(2), 3583-3598. https://doi.org/10.32604/cmc.2025.066909
Received 20 April 2025; Accepted 22 July 2025; Issue published 23 September 2025
Abstract
Rumor Control (RC), aimed at minimizing the spread of rumors in social networks, is of paramount importance, as the spread of rumors can lead to significant economic losses, societal disruptions, and even widespread panic. The RC problem has garnered extensive research attention, however, most existing solutions for rumor control face a trade-off between efficiency and effectiveness, which limits their practical application in real-world scenarios. In this light, this paper studies the Truth-spreading-based Rumor Control (TRC) problem, and introduces the Subgraph-based Greedy algorithm Optimized with CELF (SGOC), which employs subgraph techniques and the CELF strategy, as the basic solution for the TRC problem. To improve the performance of SGOC, we carefully design a shortest path length dictionary SPR and an Immune Nodes Set (INS), leading to the Shortest Path-Based Rumor Control (SPRC) algorithm. To further enhance the SPRC algorithm, we develop a pruning method that accelerates the construction process of INS, proposing the Improved Shortest Path-Based Rumor Control (ISPRC) algorithm, which demonstrates superior efficiency compared to both SPRC and SGOC. Extensive experiments conducted on five real-world datasets, demonstrate the effectiveness and efficiency of the proposed algorithms.Keywords
Cite This Article
Copyright © 2025 The Author(s). Published by Tech Science Press.This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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