Title: Modeling news spread as an SIR process over temporal networks,
Abstract: News spread in internet media outlets can be seen as a contagious process
generating temporal networks representing the influence between published
articles. In this article we propose a methodology based on the application of
natural language analysis of the articles to reconstruct the spread network.
From the reconstructed network, we show that the dynamics of the news spread
can be approximated by a classical SIR epidemiological dynamics upon the
network. From the results obtained we argue that the methodology proposed can
be used to make predictions about media repercussion, and also to detect viral
memes in news streams.