Epidemiological modeling of online social network dynamics

TL;DR

This paper applies an epidemiological SIR model with infectious recovery to understand and predict user adoption and abandonment patterns in online social networks, validated with Google search data for MySpace and Facebook.

Contribution

It introduces the irSIR model, a novel modification of the traditional SIR model, to better capture social network user dynamics and validate it with real-world search query data.

Findings

The irSIR model accurately fits MySpace's adoption and abandonment data.

The model predicts a rapid decline in Facebook activity in the near future.

Epidemiological models can effectively explain social network user behavior.

Abstract

The last decade has seen the rise of immense online social networks (OSNs) such as MySpace and Facebook. In this paper we use epidemiological models to explain user adoption and abandonment of OSNs, where adoption is analogous to infection and abandonment is analogous to recovery. We modify the traditional SIR model of disease spread by incorporating infectious recovery dynamics such that contact between a recovered and infected member of the population is required for recovery. The proposed infectious recovery SIR model (irSIR model) is validated using publicly available Google search query data for "MySpace" as a case study of an OSN that has exhibited both adoption and abandonment phases. The irSIR model is then applied to search query data for "Facebook," which is just beginning to show the onset of an abandonment phase. Extrapolating the best fit model into the future predicts a rapid decline in Facebook activity in the next few years.