368 research outputs found
Go viral or go broadcast? Characterizing the virality and growth of cascades
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 utility of the proposed virality measure. Based on preferential
attachment mechanisms, we further introduce a model to mimic the growth of
cascades. The proposed model enables the interpolation between broadcast and
viral spreading during the growth of cascades. Through numerical simulations,
we demonstrate the effectiveness of the proposed model in characterizing the
virality of growing cascades. Our work contributes to the understanding of
cascade virality and growth, and could offer practical implications in a range
of policy domains including viral marketing, infectious disease and information
diffusion.Comment: 10 pages, 15 figures, 1 tabl
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