Centrality measures such as the degree, k-shell, or eigenvalue centrality can
identify a network's most influential nodes, but are rarely usefully accurate
in quantifying the spreading power of the vast majority of nodes which are not
highly influential. The spreading power of all network nodes is better
explained by considering, from a continuous-time epidemiological perspective,
the distribution of the force of infection each node generates. The resulting
metric, the \textit{expected force}, accurately quantifies node spreading power
under all primary epidemiological models across a wide range of archetypical
human contact networks. When node power is low, influence is a function of
neighbor degree. As power increases, a node's own degree becomes more
important. The strength of this relationship is modulated by network structure,
being more pronounced in narrow, dense networks typical of social networking
and weakening in broader, looser association networks such as the Internet. The
expected force can be computed independently for individual nodes, making it
applicable for networks whose adjacency matrix is dynamic, not well specified,
or overwhelmingly large
