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The Parable of Google Flu: Traps in Big Data Analysis

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2014

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10.1126/science.1248506

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American Association for the Advancement of Science (AAAS)
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Lazer, D., R. Kennedy, G. King, and A. Vespignani. 2014. “The Parable of Google Flu: Traps in Big Data Analysis.” Science 343 (6176) (March 14): 1203–1205.

Abstract

Large errors in flu prediction were largely avoidable, which offers lessons for the use of big data. In February 2013, Google Flu Trends (GFT) made headlines but not for a reason that Google executives or the creators of the flu tracking system would have hoped. Nature reported that GFT was predicting more than double the proportion of doctor visits for influenza-like illness (ILI) than the Centers for Disease Control and Prevention (CDC), which bases its estimates on surveillance reports from laboratories across the United States ( 1, 2). This happened despite the fact that GFT was built to predict CDC reports. Given that GFT is often held up as an exemplary use of big data ( 3, 4), what lessons can we draw from this error?

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http://nrs.harvard.edu/urn-3:HUL.InstRepos:12016836

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The Parable of Google Flu: Traps… : DASH Story 2014-07-12
I am currently in the process of developing a new graduate-level course which includes a module on the promises and pitfalls of Big Data. I have to weed though so many articles to see if they are relevant and from reputable sources. It's also important to my that the articles are interesting, engaging, and stimulate the student's imagination. This meets all those criteria. Thanks for so generously sharing!
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The Parable of Google Flu: Traps… : DASH Story 2014-11-15
I am a researcher using Google Trends data to understand brand valuation. I probably would have had access to this through my own university but hopefully in the future we can all access this kind of paper freely and universities can spend the money saved elsewhere.
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The Parable of Google Flu: Traps… : DASH Story 2015-06-26
I am developing my own statistical consulting business. Skeptical of big data, I remembered hearing news coverage of poor performance of GFT. Here, I was able to read the authors' informed and constructive critique of GFT and the big data movement generally. The authors' original and complete message is considerably more informative than the news coverage was. I found their advocacy for the "all data revolution" compelling and instructive as I develop my marketing approach.
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The Parable of Google Flu: Traps… : DASH Story 2017-04-21
I am an engineer, currently unemployed with a family to support. I am preparing for job interviews and being able to read this paper to give me context was very important at a time where paying for every bit of information would have just added stress to my personal situation. Thanks for making information freely available.