Scott Detrow

Scott Detrow is a Congressional reporter for NPR. He also co-hosts the NPR Politics Podcast.

Detrow joined NPR in 2015 to cover the presidential election. He focused on the Republican side of the 2016 race, spending time on the campaign trail with Donald Trump, and also reported on the election's technology and data angles.

Detrow worked as a statehouse reporter for member stations WITF in Harrisburg, Pennsylvania, and KQED in San Francisco, California. He has also covered energy policy for NPR's StateImpact project, where his reports on Pennsylvania's hydraulic fracturing boom won a DuPont-Columbia and national Edward R. Murrow Award in 2013.

Detrow got his start in public radio at Fordham University's WFUV. He graduated from Fordham, despite spending most of his time in the newsroom, and is also working toward completing a master's degree at the University of Pennsylvania's Fels Institute of Government.

It was probably only a matter of time before we got the live-streamed campaign.

With Periscope, Vine and Snapchat, candidates have seized on new apps this cycle to produce behind-the-scenes, unfiltered moments and deliver them to voters.

On Tuesday, Kentucky Sen. Rand Paul took the trend to its inevitable conclusion and broadcast the bulk of his day on the Iowa campaign trail on the Internet.

Want to follow what the presidential candidates are saying on Facebook, but not quite ready to turn over your news feed to pleas for money, stilted memes and behind-the-scenes pics from Iowa and New Hampshire?

Interested in hearing more from, say, Donald Trump or Hillary Clinton, but a little hesitant to declare to your Facebook friends that you "like" them?

There's a hack for that!

It sounds like a politician's dream: a machine that can tell you exactly what to say to change a voter's mind.

Well, that's what a political scientist has come up with — at least, a first tentative step in that direction.

Using text from a pro-Obamacare website and testing different combinations of sentences on volunteers, an algorithm created by Northeastern University assistant professor Nick Beauchamp was able to identify optimally persuasive terms that make people more inclined to support the landmark health care law.

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