Identifying influential spreaders in complex networks based on gravity formula
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Abstract (arXiv)
How to identify the influential spreaders in social networks is crucial for accelerating/hindering information diffusion, increasing product exposure, controlling diseases and rumors, and so on. In this paper, by viewing the k-shell value of each node as its mass and the shortest path distance between two nodes as their distance, then inspired by the idea of the gravity formula, we propose a gravity centrality index to identify the influential spreaders in complex networks. The comparison between the gravity centrality index and some well-known centralities, such as degree centrality, betweenness centrality, closeness centrality, and k-shell centrality, and so forth, indicates that our method can effectively identify the influential spreaders in real networks as well as synthetic networks. We also use the classical Susceptible-Infected-Recovered (SIR) epidemic model to verify the good performance of our method.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 May 2015.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 1.
4 papers.
- 2025Critical Nodes Identification in Complex Networks: A Surveycited by 2
- 2022Vital Node Identification in Complex Networks Using a Machine Learning-Based Approachcited by 1
- 2023A Network Science perspective of Graph Convolutional Networks: A surveycited by 1
- 2023XFlow: Benchmarking Flow Behaviors over Graphscited by 0
- 2025Critical Nodes Identification in Complex Networks: A Survey8 Jul 2025
- 2023XFlow: Benchmarking Flow Behaviors over Graphs7 Aug 2023
- 2023A Network Science perspective of Graph Convolutional Networks: A survey12 Jan 2023
- 2022Vital Node Identification in Complex Networks Using a Machine Learning-Based Approach13 Feb 2022