Off the Media

Even Data Journalists Like Klein and Silver Aren’t Above Hack Tactics

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We live in a new world of “method journalism.”

In it, bright minds like Nate Silver and Ezra Klein have staked out new media territory, defined by the style in which their writers produce content. It’s supposed to be a new golden age for content, driven by hard data in Silver’s case, and simplified explanation in Klein’s.

Except of course, they’re not. It’s just the same pageview journalism dressed up with better rhetoric. The same end, just different means. Read More

Servicey

Gift Guide: The Best Books to Buy for the Technologist in Your Life

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Tubes, Andrew Blum

They make great presents, but books are deceptively difficult to give: You don’t want to buy some random bestseller off the front table at Barnes and Noble, but wander very far into the store and it’s easy to become overwhelmed with options. To lend a hand, we’ve combed through this year’s techie-targeted releases (and tossed in a couple of old favorites, as well). Read More

Fun with Stats

Even Nate Silver Can’t Predict When a Deadspin Commenter Will Get Laid

This comes up when you Google "Nate Silver baller." (Photo: Mashable)

Statistical genius and maybe-witch Nate Silver popped by Gawker Media’s sports site, Deadspin, today for a little Q&A session. Mr. Silver answered some interesting questions that have been bouncing around the web ever since his mic drop moment, wherein he accurately predicted the electoral outcome of all 50 states.

Mr. Silver wrote that he does plan to make predictions for the elections in 2014 and 2016, and that being suddenly famous is “Completely terrifying. Still, file under ‘Good Problems to Have.’” Read More

Data Mining

Nate Silver’s Sweep Is a Huge Win for ‘Big Data’

Nate Silver Map

Like “pivot” and “cloud computing,” “big data” is one of those startup buzzwords that gets thrown around indiscriminately–partly because it means different things depending on the intel you’re trying to unearth and partly because it sounds like the kind of futuristic jargon that opens doors. Using machine learning to analyze big data? We can practically see the pitch deck already!

As The Economist noted back in 2010, the deluge of large data sets unleashed by the digital age, “makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account.” Read More