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Lookup NU author(s): Dr Clement LeeORCiD,
Professor Darren Wilkinson
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Taylor & Francis, 2020.
For re-use rights please refer to the publisher's terms and conditions.
We present a hierarchical model of non-homogeneous Poisson processes (NHPP) for information diffusion on online social media, in particular Twitter retweets. The retweets of each original tweet are modelled by a NHPP, for which the intensity function is a product of time-decaying components and another component that depends on the follower count of the original tweet author. The latter allows us to explain or predict the ultimate retweet count by a network centrality-related covariate. The inference algorithm enables the Bayes factor to be computed, in order to facilitate model selection. Finally, the model is applied to the retweet data sets of two hashtags.
Author(s): Lee C, Wilkinson DJ
Publication type: Article
Publication status: Published
Journal: Journal of the American Statistical Association
Online publication date: 09/03/2019
Acceptance date: 16/02/2019
Date deposited: 09/03/2019
ISSN (print): 0162-1459
ISSN (electronic): 1537-274X
Publisher: Taylor & Francis
Data Source Location: https://doi.org/10.17634/154300-57
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