作者
Ling-ling Ma, Chuang Ma, Hai-Feng Zhang, Bing-Hong Wang
发表日期
2016/6/1
期刊
Physica A: Statistical Mechanics and its Applications
卷号
451
页码范围
205-212
出版商
North-Holland
简介
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.
引用总数
20162017201820192020202120222023202441125242945505421
学术搜索中的文章
L Ma, C Ma, HF Zhang, BH Wang - Physica A: Statistical Mechanics and its Applications, 2016