The Message or the Messenger? Inferring Virality and Diffusion Structure from Online Petition Signature Data

TL;DR

This paper introduces temporal measures to infer the virality and diffusion structure of online petitions from time-stamped data, revealing that successful petitions exhibit higher intrinsic and structural virality and challenging simple contagion assumptions.

Contribution

It develops novel temporal dynamics-based measures to infer diffusion structure and virality from incomplete data, and validates these measures using real-world petition data.

Findings

Successful petitions show higher intrinsic and structural virality.

Threshold effects challenge simple contagion models.

Simulations align with observed data.

Abstract

Goel et al. (2016) examined diffusion data from Twitter to conclude that online petitions are shared more virally than other types of content. Their definition of structural virality, which measures the extent to which diffusion follows a broadcast model or is spread person to person (virally), depends on knowing the topology of the diffusion cascade. But often the diffusion structure cannot be observed directly. We examined time-stamped signature data from the Obama White House's We the People petition platform. We developed measures based on temporal dynamics that, we argue, can be used to infer diffusion structure as well as the more intrinsic notion of virality sometimes known as infectiousness. These measures indicate that successful petitions are likely to be higher in both intrinsic and structural virality than unsuccessful petitions are. We also investigate threshold effects on petition signing that challenge simple contagion models, and report simulations for a theoretical model that are consistent with our data.