  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 $A$ and spreading
parameter $\beta$, 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.
