Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf]
by ChuckMcM on Sunday March 23, 2014 @08:00PM
(#7455830)
This is the key difference, and after 5 years it is clear that this is not a valid way to predict the flu, or even monitor it. I think it was a great experiment, and thought it was pretty creative when announced, and now it should either be retired or replaced with a new hypothesis. Because as the Mythbusters would say, this myth is busted.
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Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf]
by blauwbilgorgel on Sunday March 23, 2014 @08:59PM
(#7456053)
One article author says the idea behind GFT has merit:
I think, actually, the core idea is a terrific one.
From [1]. [1] also has professor and doctor state that her models improved after adding GFT data. Data from search behavior does not have to replace CDC data. It can improve it. No myth.
[1] http://www.npr.org/blogs/health/2014/03/13/289802934/googles...
Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf]
by mdisraeli on Sunday March 23, 2014 @08:03PM
(#7455842)
I disagree, but it depends what you mean by "the flu". If you mean hospitalisations, then yes, you're entirely right. If you mean lost productivity and population health outside of hospital, however, perhaps we need a better means to track this other than indirectly via either current stat.
Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf]
by Fomite on Monday March 24, 2014 @11:20AM
(#7458692)
The CDC also uses a outpatient physician network to report cases of influenza-like illness in the community.
Re:The Parable of Google Flu: Traps in Big Data Analysis [pdf]
by mdisraeli on Monday March 24, 2014 @09:11PM
(#7463033)
I didn't know that, thank you! I went digging to try and find exactly what figure Google were using, and exactly how CDC came up with it, but I couldn't manage to pin them down...