  Social networks are discrete systems with a large amount of heterogeneity
among nodes (individuals). Measures of centrality aim at a quantification of
nodes' importance for structure and function. Here we ask to which extent the
most central nodes can be found by purely local search. We find that many
networks have close-to-optimal searchability under eigenvector centrality,
outperforming searches for degree and betweenness. Searchability of the
strongest spreaders in epidemic dynamics tends to be substantially larger for
supercritical than for subcritical spreading.
