Rumor spreads fast in social networks and may seriously damage our society. In this article, we present a mathematical programming formulation based on integer linear programming (ILP) to minimize rumor spread by blocking a subset of nodes (called blockers) in complex social networks modeled as a linear threshold model. We also propose a modified approach which solves the top -k blockers problem with a reduced computational effort and formally proves that its performance is still optimal. Then, the presented method is evaluated for its effectiveness of containing rumor spread in four different networks and its performance is compared with a greedy-based and two centrality-based approaches. The experimental analysis shows that the ILP-based method outperforms the other three approaches and is applicable to large-scale networks.

Rumor Containment by Blocking Nodes in Social Networks

Ma Z.
Secondo
;
Li Z.
;
Giua A.
Ultimo
2023-01-01

Abstract

Rumor spreads fast in social networks and may seriously damage our society. In this article, we present a mathematical programming formulation based on integer linear programming (ILP) to minimize rumor spread by blocking a subset of nodes (called blockers) in complex social networks modeled as a linear threshold model. We also propose a modified approach which solves the top -k blockers problem with a reduced computational effort and formally proves that its performance is still optimal. Then, the presented method is evaluated for its effectiveness of containing rumor spread in four different networks and its performance is compared with a greedy-based and two centrality-based approaches. The experimental analysis shows that the ILP-based method outperforms the other three approaches and is applicable to large-scale networks.
2023
Blocking node
integer linear programming (ILP)
linear threshold model (LTM)
rumor spread
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/376263
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