Google Flu Trends, once a poster child for the power of big-data analysis, seems to be under attack. This month, in a Science magazine article, four quantitatively adept social scientists reported that Google’s flu-tracking service not only wildly overestimated the number of flu cases in the United States in the 2012-13 flu season but has also consistently overshot in the last few years. Google Flu Trends’ estimate for the 2011-12 flu season was more than 50 percent higher than the cases reported by the Centers for Disease Control and Prevention.
A lot has been written recently criticizing Goolge’s Flu Trends – a flu tracker service that predicts flu activity based on specific search terms using aggregated Google search data and estimates current flu activity around the world in near real-time. For more, read How does this work? Science magazine has recently published an article titled “The Parable of Google Flu: Traps in Big Data Analysis” and Steve Lohr has published a great piece in BITS blog of New York Times titled “Google Flu Trends: The Limits of Big Data.” It is important to note that over-estimation of flu activity in Google Flu Trends is NOT a limitation of Big Data or Analytics used for estimating the flu activity as some of the writers have suggested. Rather, it highlights importance of fourth “V” of Big Data – Veracity.
