Posts tagged big data

For months I had joked to my family that I was probably on a watch list for my excessive use of Tor and cash withdrawals […] the things I had to do to evade marketing detection looked suspiciously like illicit activities. All I was trying to do was to fight for the right for a transaction to be just a transaction, not an excuse for a thousand little trackers to follow me around. But avoiding the big-data dragnet meant that I not only looked like a rude family member or an inconsiderate friend, but I also looked like a bad citizen.,

http://time.com/83200/privacy-internet-big-data-opt-out/

Four years after the original Nature paper was published, Nature News had sad tidings to convey: the latest flu outbreak had claimed an unexpected victim: Google Flu Trends. After reliably providing a swift and accurate account of flu outbreaks for several winters, the theory-free, data-rich model had lost its nose for where flu was going. Google’s model pointed to a severe outbreak but when the slow-and-steady data from the CDC arrived, they showed that Google’s estimates of the spread of flu-like illnesses were overstated by almost a factor of two.

http://www.ft.com/cms/s/2/21a6e7d8-b479–11e3-a09a–00144feabdc0.html#axzz2xS1VXiUc

Google Flu Trends, which launched in 2008, monitors web searches across the US to find terms associated with flu activity such as “cough” or “fever”. It uses those searches to predict up to nine weeks in advance the number of flu-related doctors’ visits that are likely to be made. The system has consistently overestimated flu-related visits over the past three years, and was especially inaccurate around the peak of flu season – when such data is most useful. In the 2012/2013 season, it predicted twice as many doctors’ visits as the US Centers for Disease Control and Prevention (CDC) eventually recorded. In 2011/2012 it overestimated by more than 50 per cent.

http://www.newscientist.com/article/dn25217-google-flu-trends-gets-it-wrong-three-years-running.html#.UyK6qce7hBo