Why Do Cascade Sizes Follow a Power-Law?
Social and Information Networks
2017-04-18 v1 Computers and Society
Abstract
We introduce random directed acyclic graph and use it to model the information diffusion network. Subsequently, we analyze the cascade generation model (CGM) introduced by Leskovec et al. [19]. Until now only empirical studies of this model were done. In this paper, we present the first theoretical proof that the sizes of cascades generated by the CGM follow the power-law distribution, which is consistent with multiple empirical analysis of the large social networks. We compared the assumptions of our model with the Twitter social network and tested the goodness of approximation.
Cite
@article{arxiv.1702.05913,
title = {Why Do Cascade Sizes Follow a Power-Law?},
author = {Karol Węgrzycki and Piotr Sankowski and Andrzej Pacuk and Piotr Wygocki},
journal= {arXiv preprint arXiv:1702.05913},
year = {2017}
}
Comments
8 pages, 7 figures, accepted to WWW 2017