  Searching for influential spreaders in complex networks is an issue of great
significance for applications across various domains, ranging from the epidemic
control, innovation diffusion, viral marketing, social movement to idea
propagation. In this paper, we first display some of the most important
theoretical models that describe spreading processes, and then discuss the
problem of locating both the individual and multiple influential spreaders
respectively. Recent approaches in these two topics are presented. For the
identification of privileged single spreaders, we summarize several widely used
centralities, such as degree, betweenness centrality, PageRank, k-shell, etc.
We investigate the empirical diffusion data in a large scale online social
community -- LiveJournal. With this extensive dataset, we find that various
measures can convey very distinct information of nodes. Of all the users in
LiveJournal social network, only a small fraction of them involve in spreading.
For the spreading processes in LiveJournal, while degree can locate nodes
participating in information diffusion with higher probability, k-shell is more
effective in finding nodes with large influence. Our results should provide
useful information for designing efficient spreading strategies in reality.
