Big Data Batman is a Twitter account that takes sentences with the phrase “big data” in them, and replaces that with Batman. Like this:
New Scientist sums up a study finding that Google’s much-hyped flu tracker–where the company supposedly can predict flu outbreaks based simply volume of search queries for flu-related terms–doesn’t actually work very well.
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.
Interesting. The most surprising part of this outcome, however, is that lead author of the study is actually surprised that Google hasn’t fixed this,
The study’s lead author, David Lazer, of Northeastern University, says the fixes for Google’s problems are relatively simple – much like recalibrating weighing scales. “It’s a bit of a puzzle, because it really wouldn’t have taken that much work to substantially improve the performance of Google Flu Trends,” he says.
That wouldn’t surprise anyone who actually uses any Google products or services at all. There are dozens of simple, easy things that Google could do to improve any number of their products, including bugs that users have been complaining about for years., that Google chooses to ignore.
Why should it be any different with the flu? Clearly the problem with the flu tracker is the influenza virus’ unwillingness to conform to Google’s business practices rather than any actual defect in its software or approach to predicting flu cases.