This session introduces the idea of currentness as a measure of quality. That is, how up-to-date are our articles? How quickly after an event/discovery is Wikipedia updated to reflect it?
Anecdotally, Wikipedia seems to be "current" for topics of broad popular interest, but currentness lags for the sort of diverse articles which fall into knowledge gaps on our projects. But can we quantify this?
In particular, I would like to discuss the use of machine translation to both measure and hopefully improve currentness. Machine translation on the recent changes feed can compute similarity scores to determine if an edit to (say) the English Wikipedia article Moons of Saturn is mirrored by a corresponding edit to the Spanish Wikipedia article Satélites de Saturno.
Moving further, the same infrastructure could suggest appropriate edits to a Wikipedia based on the recent changes feed of a Wikipedia in a different language. This could be used to improve currentness on small wikis (by importing the changes from a big wiki) and on big wikis (by importing changes to material in the big wiki's "knowledge gap" from the small wiki).
I hope participants in the discussion will bring other ideas for measuring and improving the currentness of our content.
Each Space at Wikimania 2019 will have specific format requests. The program design prioritises submissions which are future-oriented and directly engage the audience. The format of this submission is a: