Despite decades of work on the network structures underlying social influence, standard measures of node centrality frequently misidentify the most influential nodes in a network. Meanwhile, these standard measures continue to be widely employed in policy-relevant domains, from marketing to public health, for the purpose of identifying influential “seed” nodes for initiating the spread of behavior. In this work, we identify a key assumption in prior network-based measures of node centrality and social distance that significantly limit their capacity to characterize social influence. Standard measures of mode centrality often assume a “simple” model of contagion, in which individuals only require exposure to one activated peer to adopt. Yet, many social contagions are “complex,” for which people require exposure to multiple activated peers. In this study, we provide novel topological measures of “complex path length” and “complex centrality”, which identify seeds that maximize the spread of social contagions.