The Simple Rules of Social Contagion

TL;DR

This paper challenges the simple pathogen model of social contagion, showing that message visibility and interface position significantly influence information spread on social media, and proposes a model for better prediction of user behavior.

Contribution

It introduces a new model that accounts for message visibility and interface effects, improving understanding and forecasting of social contagion dynamics.

Findings

Message position on interface affects contagion likelihood

Visibility accounts for simplified contagion dynamics

Explicit feedback increases sharing probability

Abstract

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is significantly more complex than the prediction of the pathogen model. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of the exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We apply our model to real-time forecasting of user behavior.