Comparison of news commonality and churn in international news outlets with TARO

TARO is a formal model plus proof-of-concept scraping-and-NLP pipeline that compares pieces of news across outlets, languages and time windows using snapshot extensions, and it is validated on two case studies measuring news commonality (skipped/common/exclusive) and news churn rates across six Euro

Giuseppe Carrino (University of Bologna, Bologna, Italy), Angelo Di Iorio (University of Bologna, Bologna, Italy), and Gioele Barabucci (Norwegian University of Science and Technology, Trondheim, Norway). All authors contributed equally to this research.

4 September 2023

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