The paper is devoted to the effective information spreading
in random complex networks. Our objective is to elect leader nodes or
communities of the network, which may spread the content among all
nodes faster. We consider a well-known SPREAD algorithm by Mosk-
Aoyama and Shah (2006), which provides the spreading and the growth
of the node set possessing the information. Assuming that all nodes have
asynchronous clocks, the next node is chosen uniformly among nodes
of the network by the global clock tick according to a Poisson process.
The extremal index measures the clustering tendency of high threshold
exceedances. The node extremal index shows the ability to attract highly
ranked nodes in the node orbit. Considering a closeness centrality as a
measure of a node’s leadership, we find the relation between its extremal
index and the minimal spreading time.
