TL;DR
This paper introduces a root-aware virality metric for cascades, accounting for the diffusion source, and presents a model that interpolates between broadcast and viral growth, enhancing understanding of cascade dynamics.
Contribution
It proposes a novel root-aware virality measure and a growth model that captures the transition between broadcast and viral spreading in cascades.
Findings
The root-aware virality measure effectively distinguishes cascade types.
The growth model accurately mimics cascade evolution from broadcast to viral.
Numerical simulations validate the model's ability to characterize cascade virality.
Abstract
Quantifying the virality of cascades is an important question across disciplines such as the transmission of disease, the spread of information and the diffusion of innovations. An appropriate virality metric should be able to disambiguate between a shallow, broadcast-like diffusion process and a deep, multi-generational branching process. Although several valuable works have been dedicated to this field, most of them fail to take the position of the diffusion source into consideration, which makes them fall into the trap of graph isomorphism and would result in imprecise estimation of cascade virality inevitably under certain circumstances. In this paper, we propose a root-aware approach to quantifying the virality of cascades with proper consideration of the root node in a diffusion tree. With applications on synthetic and empirical cascades, we show the properties and potential…
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