The New York Times is testing a new tool that recommends stories based on their popularity on Twitter. Dubbed Vellum, “The feature teases out the links shared by people you follow and ranks them
by frequency,” Capital New York reports. Developed by The New York Times R&D lab, Vellum “flips the Twitter model, treating the links as primary and the commentary as secondary,”
according to NYTimes Labs creative director Alexis Lloyd.
Read the whole story at Capital New York »