Detecting textual reuse in news stories, at scale - Nicholls, T (University of Southern California, Annenberg School for Communication & Journalism, 2019)
Motivated by the debate around “churnalism” and online media, this paper develops, evaluates, and validates a computational method for detecting shared text between different news articles, at scale, using n-gram shingling. We differentiate between newswire copy, public relations material, source-to-source copying, and common-source and incidental overlaps. We evaluate the method, quantitatively and qualitatively, and show that it can effectively handle newswire content, copying, and other forms of reuse. Substantively, we find lower levels of news agency and press release copy reuse than suggested by previous studies. We conclude that the news agency finding is robust, but the lack of press release copy found might reflect limitations of the method and the changing practices of journalists.