2023/09/09 by Changan Liu, Liu, Changan, Xiaotian Zhou +5 · 2 citations
Computer Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Complex Network Analysis Techniques #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Mobile Ad Hoc Networks #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2309.06392
openalex publication_date 2023/09/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Critical nodes in networks are extremely vulnerable to malicious attacks to trigger negative cascading events such as the spread of misinformation and diseases. Therefore, effective moderation of critical nodes is very vital for mitigating the potential damages caused by such malicious diffusions. The current moderation methods are computationally expensive. Furthermore, they disregard the fundamental metric of information centrality, which measures the dissemination power of nodes. We investigate the problem of removing k edges from a network to minimize the information centrality of a target node \lea while preserving the network's connectivity. We prove that this problem is computationally challenging: it is NP-complete and its objective function is not supermodular. However, we propose three approximation greedy algorithms using novel techniques such as random walk-based Schur complement approximation and fast sum estimation. One of our algorithms runs in nearly linear time in the number of edges. To complement our theoretical analysis, we conduct a comprehensive set of experiments on synthetic and real networks with over one million nodes. Across various settings, the experimental results illustrate the effectiveness and efficiency of our proposed algorithms.