  Although recent studies show that both topological structures and human
dynamics can strongly affect information spreading on social networks, the
complicated interplay of the two significant factors has not yet been clearly
described. In this work, we find a strong pairwise interaction based on
analyzing the weighted network generated by the short message communication
dataset within a Chinese tele-communication provider. The pairwise interaction
bridges the network topological structure and human interaction dynamics, which
can promote local information spreading between pairs of communication partners
and in contrast can also suppress global information (e.g., rumor) cascade and
spreading. In addition, the pairwise interaction is the basic pattern of group
conversations and it can greatly reduce the waiting time of communication
events between a pair of intimate friends. Our findings are also helpful for
communication operators to design novel tariff strategies and optimize their
communication services.
