  The paper addresses a method for spreading messages in social networks
through an initial acceleration by Spreading Groups. These groups start the
spread which eventually reaches a larger portion of the network. The use of
spreading groups creates a final flow which resembles the spread through the
nodes with the highest level of influence (opinion leaders). While harnessing
opinion leaders to spread messages is generally costly, the formation of
spreading groups is merely a technical issue, and can be done by computerized
bots. The paper presents an information flow model and inspects the model
through a dataset of Nasdaq-related tweets.
