s Google’s Flu Trends (GFT) tracking system a failure of big data?

A new article pub­lished this after­noon in Sci­ence mag­a­zine sug­gests that Google’s much-​​covered algo­rithmic Flu Trends model, used to mon­itor search queries to track the spread of the flu, has rou­tinely failed to accu­rately pre­dict flu preva­lence since it’s incep­tion in 2008. While the report is another set­back for Google (a 2013 article in the sci­ence journal Nature came to a sim­ilar con­clu­sion about GFT’s accu­racy), GFT’s fail­ures rep­re­sent a bigger struggle for data-​​driven research and threaten to cast a shadow on the broader, much-​​hyped con­cept of big data.

In late 2008, Google announced Google Flu Trends to a series of cau­tiously opti­mistic early reviews. The New York Times described it as “what appears to be a fruitful mar­riage of mob behavior and med­i­cine” and many held out hope that Google’s algo­rithm could out­per­form CDC data models, which have long been held as the stan­dard for flu detec­tion and prediction.

Read the article at Buzzfeed →