ABSTRACT
This chapter considers computational journalism to be the advanced application of computing, algorithms, and automation to the gathering, evaluation, composition, presentation, and distribution of news. Computational news gathering and evaluation can utilize tools that find and filter newsworthy information from social media platforms and document caches and that provide guidance on the credibility of content and contributors. Computational journalism is a relatively new term. It was coined in 2006 by Irfan Essa when he organized the first course on the subject alongside Nick Diakopoulos at Georgia Tech. Computational news gathering—at least at scale—also took a while to take off but has now done so, driven by the increasing volumes of digital data, including on social media platforms, that contain potentially newsworthy nuggets. The use of computation in personalized news distribution—and the academic and popular discourse around it—has a substantially longer history than sensor journalism.
