Weighted H-index for identifying influential spreaders
arXiv:1710.05272
Abstract
Spreading is a ubiquitous process in the social, biological and technological systems. Therefore, identifying influential spreaders, which is important to prevent epidemic spreading and to establish effective vaccination strategies, is full of theoretical and practical significance. In this paper, a weighted h-index centrality based on virtual nodes extension is proposed to quantify the spreading influence of nodes in complex networks. Simulation results on real-world networks reveal that the proposed method provides more accurate and more consistent ranking than the five classical methods. Moreover, we observe that the monotonicity and the computational complexity of our measure can also yield excellent performance.
References in corpus (13)
- Cooperative Game Theory Approaches for Network Partitioning
- Epidemic processes in complex networks
- Identification of influential spreaders in complex networks
- Benchmark graphs for testing community detection algorithms
- Self-similar community structure in organisations
- Dynamics of Rumor Spreading in Complex Networks
- Cascade control and defense in complex networks
- Thresholds for epidemic spreading in networks
- Centrality in Interconnected Multilayer Networks
- Ranking spreaders by decomposing complex networks
- Ranking the spreading influence in complex networks
- Robust classification of salient links in complex networks
- Accurate ranking of influential spreaders in networks based on dynamically asymmetric link-impact