Investigating news coverage and circulation over time in a quantitative manner: the TARO framework

Nowadays news spread all over the world at incredible speed, thanks to news channels and social media. This is of great value not only for readers, who benefit from a huge amount of available information, and publishers, who gain visibility and connections but also for scholars who can investigate publication processes and public debate in depth. This paper presents a framework for studying news circulation in quantitative and computational terms. The framework is called TARO and is able to capture how “the same news” has been treated by different outlets, in different languages and in different moments in time. The key contribution of TARO is the capability to collect and process hard data about online news publishing processes, and to be easily adaptable to multiple sources and target analyses. This article in particular presents the details of the whole TARO framework—including the core conceptual model and some recent extensions, together with a software implementation—and shows how TARO can be successfully used to compare strategies for publishing and re-publishing news over time.