Identifying Influential Spreaders by Weighted LeaderRank
Physics and Society
2015-01-16 v2 Social and Information Networks
Data Analysis, Statistics and Probability
Abstract
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 [L. Lv et al., PLoS ONE 6 (2011) e21202]. 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.
Cite
@article{arxiv.1306.5042,
title = {Identifying Influential Spreaders by Weighted LeaderRank},
author = {Qian Li and Tao Zhou and Linyuan Lv and Duanbing Chen},
journal= {arXiv preprint arXiv:1306.5042},
year = {2015}
}
Comments
15 pages and 8 figures