Conjoining Speeds up Information Diffusion in Overlaying Social-Physical Networks

TL;DR

This paper analyzes how combining physical and online social networks accelerates and amplifies information spread, showing that their integration can lead to larger and faster epidemics even when individual networks do not percolate.

Contribution

It introduces a model for information diffusion in overlaying social-physical networks and demonstrates that conjoining these networks significantly enhances epidemic size and speed.

Findings

Percolation can occur in the combined network even if absent in individual networks.

The fraction of informed individuals is much larger in the combined network.

Integration of physical and online networks dramatically accelerates information diffusion.

Abstract

We study the diffusion of information in an overlaying social-physical network. Specifically, we consider the following set-up: There is a physical information network where information spreads amongst people through conventional communication media (e.g., face-to-face communication, phone calls), and conjoint to this physical network, there are online social networks where information spreads via web sites such as Facebook, Twitter, FriendFeed, YouTube, etc. We quantify the size and the critical threshold of information epidemics in this conjoint social-physical network by assuming that information diffuses according to the SIR epidemic model. One interesting finding is that even if there is no percolation in the individual networks, percolation (i.e., information epidemics) can take place in the conjoint social-physical network. We also show, both analytically and experimentally, that the fraction of individuals who receive an item of information (started from an arbitrary node) is significantly larger in the conjoint social-physical network case, as compared to the case where the networks are disjoint. These findings reveal that conjoining the physical network with online social networks can have a dramatic impact on the speed and scale of information diffusion.