Pairwise interaction pattern in the weighted communication network

TL;DR

This paper uncovers a strong pairwise interaction pattern in weighted communication networks that influences local and global information spreading, with implications for optimizing communication services.

Contribution

It identifies and analyzes the pairwise interaction pattern in weighted communication networks, revealing its role in information spreading and communication efficiency.

Findings

Pairwise interaction promotes local information exchange.

It suppresses large-scale rumor spreading.

Reduces waiting time between communication events.

Abstract

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.