Identifying influential spreaders is crucial for understanding and controlling spreading processes on social networks. Via assigning degree-dependent weights onto links associated with the ground node, we proposed a variant to a recent ranking algorithm named LeaderRank (Lü et al., 2011). According to the simulations on the standard SIR model, the weighted LeaderRank performs better than LeaderRank in three aspects: (i) the ability to find out more influential spreaders; (ii) the higher tolerance to noisy data; and (iii) the higher robustness to intentional attacks. © 2014 Elsevier B.V. All rights reserved.
CITATION STYLE
Li, Q., Zhou, T., Lü, L., & Chen, D. (2014). Identifying influential spreaders by weighted LeaderRank. Physica A: Statistical Mechanics and Its Applications, 404, 47–55. https://doi.org/10.1016/j.physa.2014.02.041
Mendeley helps you to discover research relevant for your work.