English

A general method for identifying node spreading influence via the adjacent matrix and spreading rate

Physics and Society 2014-08-27 v1 Social and Information Networks Data Analysis, Statistics and Probability

Abstract

With great theoretical and practical significance, identifying the node spreading influence of complex network is one of the most promising domains. So far, various topology-based centrality measures have been proposed to identify the node spreading influence in a network. However, the node spreading influence is a result of the interplay between the network topology structure and spreading dynamics. In this paper, we build up the systematic method by combining the network structure and spreading dynamics to identify the node spreading influence. By combining the adjacent matrix AA and spreading parameter β\beta, we theoretical give the node spreading influence with the eigenvector of the largest eigenvalue. Comparing with the Susceptible-Infected-Recovered (SIR) model epidemic results for four real networks, our method could identify the node spreading influence more accurately than the ones generated by the degree, K-shell and eigenvector centrality. This work may provide a systematic method for identifying node spreading influence.

Keywords

Cite

@article{arxiv.1408.6030,
  title  = {A general method for identifying node spreading influence via the adjacent matrix and spreading rate},
  author = {Jian-Hong Lin and Jian-Guo Liu and Qiang Guo},
  journal= {arXiv preprint arXiv:1408.6030},
  year   = {2014}
}

Comments

5 pages, 4 figures

R2 v1 2026-06-22T05:39:49.178Z