Wikimedia Foundation data scientists are using machine learning to predict whether—and why—any given sentence on Wikipedia may need a citation in order to help editors identify areas of content violating the verifiability policy.

And other recent research papers.

A recap of recent research in our realm

Plus: new Wiki Studies journal, Wikipedia usage on Twitter and more

New research about Wikipedia and Wikimedia projects.

Wikipedia's articles on drugs are pretty good – good enough to impress even doctors. A new research study adds some substance to that impression.

Wikipedians' "encyclopedic identity" dominates even in Kosovo debates: Have you wondered about differences in the articles on Crimea in the Russian, Ukrainian, and English versions of Wikipedia? A newly published article entitled "Lost in Translation: Contexts, Computing, Disputing on Wikipedia" doesn't address Crimea, but nonetheless offers insight into the editing of contentious articles in multiple language editions through a heavy qualitative examination of Wikipedia articles about the Kosovo in the Serbian, Croatian, and English editions.

An author experimented with "a promising type of assignment in formal translator training which involves translating and publishing Wikipedia articles", in three courses with students at the University of Warsaw.

A conference paper makes a rather serious claim: "We find a surprisingly large number of editors who change their behavior and begin focusing more on a particular controversial topic once they are promoted to administrator status."

An ArXiv preprint titled "Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles" is about the Wikipedia articles on individuals and their position in the hyperlink network of the articles in each Wikipedia language edition, considering the whole hyperlink network.