Maximizing spreading influence via measuring influence overlap for social networks
Social and Information Networks
2019-03-04 v1 Physics and Society
Abstract
Influence overlap is a universal phenomenon in influence spreading for social networks. In this paper, we argue that the redundant influence generated by influence overlap cause negative effect for maximizing spreading influence. Firstly, we present a theoretical method to calculate the influence overlap and record the redundant influence. Then in term of eliminating redundant influence, we present two algorithms, namely, Degree-Redundant-Influence (DRS) and Degree-Second-Neighborhood (DSN) for multiple spreaders identification. The experiments for four empirical social networks successfully verify the methods, and the spreaders selected by the DSN algorithm show smaller degree and k-core values.
Cite
@article{arxiv.1903.00248,
title = {Maximizing spreading influence via measuring influence overlap for social networks},
author = {Ning Wang and Zi-Yi Wang and Jian-Guo Liu and Jing-Ti Han},
journal= {arXiv preprint arXiv:1903.00248},
year = {2019}
}
Comments
20 pages, 6 figures