The authors, academics from Northeastern University, Harvard University, and the University of Houston, concluded that Google Flu Trends had wildly overestimated the number of flu cases in the United States for more than two years. The article, "The Parable of Google Flu: Traps in Big Data Analysis," concluded that the errors were, at least in part, due to the decisions made by GFT engineers about what to include in their models-mistakes the academics dubbed "algorithmic dynamics" and "big data hubris.
( Clayton M. Christensen )
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