Megan Garber: "[In] a fascinating paper [pdf] from UCLA and Hewlett-Packard's HP Labs ... researchers Roja Bandari, Sitram Asur, and Bernardo Huberman teamed up to try to predict the popularity -- which is to say, the spreadability -- of news articles in the social space. While previous work has relied on articles' early performance to predict their popularity over their remaining lifespan, Bandari et al focused on predicting their popularity even before they're formulated in the first place. The researchers have developed a tool that allows people -- and, in particular, news organizations -- to calibrate their content in advance of their posting and tweeting, creating stuff that's optimized for maximum attention and impact. That tool allows for the forecasting of an article's popularity with a remarkable 84 percent accuracy -- and it has implications not just for articles, but for tweets themselves." - martinstabe