ABSTRACT
Social networks are a major gateway to access news content. It is estimated that a third of all web visits originate on social media, and about half of users rely on those to keep up-to-date with world events. Strangely, no model has been proposed and validated to study how to reproduce and interpolate clicks created by social media. Here we study news posted on Twitter, leveraging public information as well as private data from a popular online publisher. We propose and validate a simple two-step model of information diffusion that can be easily interpreted and applied using only public information to determine current and future clicks.
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Index Terms
- Dynamics and Prediction of Clicks on News from Twitter
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