Social media platforms face challenges from the rapid spread of rumors, impacting public safety and democracy. Existing approaches like suspending users or broadcasting real information are costly and disruptive. A new approach is introduced, minimizing user disturbance by intervening in the social network to slow rumor propagation. A knowledge-informed agent is developed using graph neural networks and policy networks for link selection. Experiments show over 25% reduction in affected populations. The proposed method is released as open-source code.
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