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I thought I was publishing an entertaining view of some data I’d extracted, but it was treated like a scientific study.


http://petewarden.com/2013/07/18/why-you-should-never-trust-a-data-scientist/

My first taste of this was my Facebook friends connection map. The underlying data was sound, derived from 220m public profiles. The network visualization of drawing lines between the top ten links for each city had issues, but was defensible. The clustering was produced by me squinting at all the lines, coloring in some areas that seemed more connected in a paint program, and picking silly names for the areas. I thought I was publishing an entertaining view of some data I’d extracted, but it was treated like a scientific study. A New York Times columnist used it as evidence that the US was perilously divided. White supremacists dug into the tool to show that Juan was more popular than John in Texan border towns, and so the country was on the verge of being swamped by Hispanics. 

lying statistics

There’s a mass of fascinating information buried in all the data we’re collecting on ourselves, and traditional scientists have been painfully slow to take advantage of it. There are all sorts of barriers, ranging from the proprietary nature of the source data, the lack of familiarity with methods able to handle the information at scale, and a cultural distance between the academic and startup worlds. None of these should be insurmountable though. There’s great work being done with confidential IRS and US Census data, so the protocols exist to both do real science and preserve secrecy. I’ve seen the size of the fiber-optic bundles at CERN, so physicists at least know how to deal with crazy data rates. Most of the big startups had their roots in universities, so the cultural gap should be bridgeable.

Stashed in: Big Data!, Pants on fire!, Big Data

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