Google Flu Trends Still Appears Sick: An Evaluation of the 2013-2014 Flu Season
Northeastern University - Department of Political Science; Harvard University - Harvard Kennedy School (HKS)
University of Houston - Department of Political Science
March 13, 2014
In response to its poor performance during the 2012-2013 flu season, Google Flu Trends (GFT) engineers announced a redesign of the GFT algorithm. Two changes were made: (1) dampening anomalous media spikes and (2) using ElasticNet, rather than regression, for estimation. This paper identifies several problems that persist in the new algorithm. First, the transparency problems identified in our earlier Science paper appear to have, if anything, become worse. Second, there are reasons to doubt whether a spike in media attention was the only, or primary, cause of GFT's errors. Finally, there is strong evidence that GFT is still not using all the information at its disposal to make accurate measurements of flu prevalence. While it is too early to give a complete evaluation of the new algorithm, these results are discouraging.
Number of Pages in PDF File: 11
Keywords: Google Flu Trends, big data, transparency, replication, time series
JEL Classification: C22, I1, I18working papers series
Date posted: March 14, 2014
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